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Caacutetedra de geneacutetica
Universidad Nacional Autoacutenoma de ColombiaSede Bogotaacute
Layla Michaacuten
Departamento de Biologiacutea Evolutiva Facultad de Ciencias UNAM
(r)evolucioacuten de informacioacuten en biologiacutea el caso de la genoacutemica
INFORMACIOacuteNBIOLOacuteGICA
TIPOS1Bioloacutegica2Bibliograacutefica3Institucional
AacuteREAS1Biodiversidad2Biomedicina
APLICACIONES1Obtencioacuten de nuevo conocimiento (Biologiacutea)2Anaacutelisis de la ciencia actual (Bibliometriacutea Historia Sociologiacutea)3Ciencias de la Informacioacuten y la documentacioacuten bioloacutegica4Planeacioacuten evaluacioacuten gestioacuten y poliacutetica cientiacutefica
PROBLEMAS1 (R)evolucioacuten digital en las ciencias bioloacutegicas2 Caracteriacutesticas de la E-biologiacutea3 Dinaacutemica estructura y relaciones de la biologiacutea reciente4 Publicacioacuten cientiacutefica5 Recursos web y ciberinfraestructura para biologiacutea6 Colecciones de datos7 Meta-anaacutelisis de literatura bibliometriacutea anaacutelisis de redes mineriacutea de textos semaacutentica
ENFOQUES1Biologiacutea2Ciencias de la informacioacuten y documentacioacuten3Tecnologiacuteas de la Informacioacuten y comunicacioacuten4Ciencias de la computacioacuten
Historia de la cienciasEtapas
bull Antiguumledad (III ac V dc)
bull Edad Media(V-XIV)
bull Renacimiento (XV-XVI)
bull Etapa Moderna Temprana (XVII-XVIII)
bull Etapa Moderna (1800-1950)
bull Etapa Reciente o Contemporaacutenea(1950-2010)
Historia Biologiacutea (Problemas)
Historia Natural (in vivo)
ndash Siglo III AC-XIX
BiologiacuteaSiglo XX (in vitro)
Molecularizacioacuten
Siglo XXI (in silico)Computarizacioacuten
Los problemas de la Herencia Siglo XIX
bull La biologiacutea es una rama del conocimiento derivada de la siacutentesis de diversas tradiciones cientiacuteficas sin duda la maacutes importante es la Historia Natural pero durante el siglo XIX hubo otras quizaacutes menos abundantes en cuanto a produccioacuten pero igualmente relevantes en cuanto a las innovaciones conceptuales para la biologiacutea actual entre estas estaacuten
bull La herencia que estudiaba como se transmiten los caracteres de los padres a los hijos con base en
ndash La de los criadores y mejoradores enfocados al estudio del mejoramiento (especialmente de plantas) es decir en la herencia de los caracteres importantes para el hombre (agronomiacutea actual)
ndash La de los hibridoacutelogos encargados de estudiar la herencia de caracteres y la naturaleza de la especie (esencialista y nominalista) iniciada con Linneo
bull Habiacutea dos formas de estudiar la herencia de caracteres
ndash Los arboles genealoacutegicos o pedigriacutes
ndash Cruzas entre individuos con distintos caracteres
Gregor Mendel (1822-1884)bull En 1900 se redescubrioacute el trabajo de Gregor Mendel quien en 1865 habiacutea
anunciado el resultado de sus estudios con chiacutecharos ante la Sociedad
Bruniana
bull Los principales postulados de sus experimentos fueron
ndash Ciertos caracteres que pueden distinguirse faacutecilmente muestran
predominancia de unos sobre otros en la progenie de la cruza de padres
con caracteres opuestos o diferenciados
ndash Dos caracteres son transmitidos como elementos diferentes uno del padre
y otro de la madre en donde uno es dominante y el otro recesivo Los
caracteres que se transmiten y aparecen en la primera generacioacuten son los
dominantes y los que permanecen ocultos o de forma latente en el proceso
son los recesivos
bull Mendel usoacute la expresioacuten recesivo porque estos caracteres desaparecen en la
primera generacioacuten pero reaparecen en las subsecuentes
bull Reconocioacute que esos pares actuacutean independientemente de otros pares de
caracteres
bull De estos dos principios derivoacute algunas reglas aritmeacuteticas que rigen la herencia
Para progenies de hiacutebridos con un par de caracteres diferenciantes) R y r su
proporcioacuten de la progenie seraacute de tres dominantes contra un recesivo
Cuando difieren en dos pares de caracteres la proporcioacuten seraacute de 9331
Redescubrimiento de las leyes de Mendel
En 1900 de manera independiente publicaron los resultados de sus trabajos haciendo referencia al trabajo ldquoprecursorrdquo de Mendel
bull El botaacutenico holandeacutes Hugo de Vries (1848-1935)
bull El botaacutenico alemaacuten Carl Correns (1864-1933)
bull El austriacuteaco Eric Tschermak von Seysenegg (1871-1962)
Este hecho marcoacute el inicio del estudio de la geneacutetica se extendieron y aplicaron los conocimientos mendelianos
bull Soacutelo Correns comprendioacute completamente el trabajo de Mendel y sus consecuencias Tanto De Vries como Tschermak no entendiacutean conceptos como dominancia y confundiacutean en una las dos leyes de Mendel en una sola Es entonces muy claro que el trabajo de Mendel no fue entendido ni en sus aspectos teacutecnicos ni tampoco en su importancia De hecho el entendimiento de su relevancia vino antes de ser entendido teacutecnicamente
Tomas H Morgan (1866-1945)
Teoriacutea cromosoacutemica de la herencia
Mapas cromosoacutemicos
Herencia ligada al sexo
Nobel 1933
El teacutermino biologiacutea molecular fue acuntildeado por el Director de la
Divisioacuten de Ciencias Naturales de la fundacioacuten Rokefeller Warren
Weaver en 1938
Warren Weaver
(1894-1978)Warren Weaver Hall
Washington
Hechos histoacutericos httpwwwnaturecomnaturejournalv422n6934pdftimeline_01626pdf
James Watson y Francis Crick
Premio Nobel 1962
1990 TICS Y BIOLOGIacuteA
La sociedad del conocimiento
bull Se refiere al incremento espectacular y a la aceleracioacuten sin precedente del ritmo de creacioacuten acumulacioacuten distribucioacuten y aprovechamiento de la informacioacuten y el conocimiento
-El conocimiento se crea se acumula se difunde y se aprovecha pues orienta las decisiones y permite la intervencioacuten en el mundo de acuerdo con ciertos fines y valores (Morales 2001)
bull El modelo de la Sociedad del Conocimiento estaacute en construccioacuten al igual que la sociedad misma (Oliveacute 2005)
(Re)evolucioacuten de la informacioacuten (1990)
bull Disentildeo de las computadoras
bull Aparicioacuten del Internet
bull Masificacioacuten de la web
bull Formato digital bajo costo poco espacio
bull Explosioacuten de la informacioacuten
bull Gran cantidad de colecciones de datos
bull Dinaacutemica cambia estaacute en modificacioacuten constante tanto el contenido como los formatos
bull Masiva
bull Aplicaciones de mata-anaacutelisis
(Re)evolucioacuten de la informacioacuten (cientiacutefica)bull La adopcioacuten del formato electroacutenico
bull Produccioacuten acelerada de una gran variedad de programas aplicaciones herramientas utilidades recursos y servicios electroacutenicos para la praacutectica cientiacutefica muchos de ellos disponibles a traveacutes de la Internet
bull Uso de la Web como medio de comunicacioacuten
bull El nuacutemero de los investigadores y de sus publicaciones se duplica aproximadamente cada veinte antildeos
bull Viven actualmente entre un 80 y un 90 de los cientiacuteficos que han existido
bull Se publican cada antildeo mas de dos millones de artiacuteculos
bull Se conceden un milloacuten de patentes
bull Modificacioacuten en la forma de producir evaluar y consultar la informacioacuten
ndash Revistas electroacutenicas
ndash Procedimiento electroacutenico
ndash Evaluacioacuten libre
ndash E-prints Preprints y posprints
ndash Inmediatez
bull Se han producido nuevas disciplinas cientiacuteficas
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
Comparacioacuten
Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
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2005
Escherichia (94873)
Drosophila (48989)
Saccharomyces (27549)
Arabidopsis (18094)
Caenorhabditis (5353)
Year
Docu
men
ts
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Zea (7636)
Neurospora (6640)
Dictyostelium (6191)
Chlamydomonas (5646)
Schizosaccharomyces (3183)
Danio (973)
Year
Docu
men
tos
Figure 21
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Ge
ne
tics amp H
ere
dity
Bio
che
m amp
Mo
l Bio
Ce
ll Bio
De
velo
p B
io
Mu
ltidiscip
linary
Ne
uro
scien
ces
Bio
logy
Zoo
logy
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tion
ary Bio
Ecolo
gy
Ento
mo
logy
Toxico
logy
Ph
ysiolo
gy
Bio
ph
ysics
Bio
tech
amp M
icrob
io
Be
havio
ral Scien
Do
cum
en
ts
Subject Area
12581258 1231 1200 782 706
10907
8137
4310
2519 2482 2365 23401811
1465
6328
17900
(2)(1)
(20)
(3)
(15)
(18)
(6)
(3)(2)
Figure 22
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Genetics amp Heredity
Biochemistry amp Molecular Biology
Cell Biology
Developmental Biology
Neuroscience
Year
Docu
men
ts
Figure 23
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00
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Evolutionary Biology
Ecology
Zoology
Toxicology
Year
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men
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
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1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
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blic
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Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
INFORMACIOacuteNBIOLOacuteGICA
TIPOS1Bioloacutegica2Bibliograacutefica3Institucional
AacuteREAS1Biodiversidad2Biomedicina
APLICACIONES1Obtencioacuten de nuevo conocimiento (Biologiacutea)2Anaacutelisis de la ciencia actual (Bibliometriacutea Historia Sociologiacutea)3Ciencias de la Informacioacuten y la documentacioacuten bioloacutegica4Planeacioacuten evaluacioacuten gestioacuten y poliacutetica cientiacutefica
PROBLEMAS1 (R)evolucioacuten digital en las ciencias bioloacutegicas2 Caracteriacutesticas de la E-biologiacutea3 Dinaacutemica estructura y relaciones de la biologiacutea reciente4 Publicacioacuten cientiacutefica5 Recursos web y ciberinfraestructura para biologiacutea6 Colecciones de datos7 Meta-anaacutelisis de literatura bibliometriacutea anaacutelisis de redes mineriacutea de textos semaacutentica
ENFOQUES1Biologiacutea2Ciencias de la informacioacuten y documentacioacuten3Tecnologiacuteas de la Informacioacuten y comunicacioacuten4Ciencias de la computacioacuten
Historia de la cienciasEtapas
bull Antiguumledad (III ac V dc)
bull Edad Media(V-XIV)
bull Renacimiento (XV-XVI)
bull Etapa Moderna Temprana (XVII-XVIII)
bull Etapa Moderna (1800-1950)
bull Etapa Reciente o Contemporaacutenea(1950-2010)
Historia Biologiacutea (Problemas)
Historia Natural (in vivo)
ndash Siglo III AC-XIX
BiologiacuteaSiglo XX (in vitro)
Molecularizacioacuten
Siglo XXI (in silico)Computarizacioacuten
Los problemas de la Herencia Siglo XIX
bull La biologiacutea es una rama del conocimiento derivada de la siacutentesis de diversas tradiciones cientiacuteficas sin duda la maacutes importante es la Historia Natural pero durante el siglo XIX hubo otras quizaacutes menos abundantes en cuanto a produccioacuten pero igualmente relevantes en cuanto a las innovaciones conceptuales para la biologiacutea actual entre estas estaacuten
bull La herencia que estudiaba como se transmiten los caracteres de los padres a los hijos con base en
ndash La de los criadores y mejoradores enfocados al estudio del mejoramiento (especialmente de plantas) es decir en la herencia de los caracteres importantes para el hombre (agronomiacutea actual)
ndash La de los hibridoacutelogos encargados de estudiar la herencia de caracteres y la naturaleza de la especie (esencialista y nominalista) iniciada con Linneo
bull Habiacutea dos formas de estudiar la herencia de caracteres
ndash Los arboles genealoacutegicos o pedigriacutes
ndash Cruzas entre individuos con distintos caracteres
Gregor Mendel (1822-1884)bull En 1900 se redescubrioacute el trabajo de Gregor Mendel quien en 1865 habiacutea
anunciado el resultado de sus estudios con chiacutecharos ante la Sociedad
Bruniana
bull Los principales postulados de sus experimentos fueron
ndash Ciertos caracteres que pueden distinguirse faacutecilmente muestran
predominancia de unos sobre otros en la progenie de la cruza de padres
con caracteres opuestos o diferenciados
ndash Dos caracteres son transmitidos como elementos diferentes uno del padre
y otro de la madre en donde uno es dominante y el otro recesivo Los
caracteres que se transmiten y aparecen en la primera generacioacuten son los
dominantes y los que permanecen ocultos o de forma latente en el proceso
son los recesivos
bull Mendel usoacute la expresioacuten recesivo porque estos caracteres desaparecen en la
primera generacioacuten pero reaparecen en las subsecuentes
bull Reconocioacute que esos pares actuacutean independientemente de otros pares de
caracteres
bull De estos dos principios derivoacute algunas reglas aritmeacuteticas que rigen la herencia
Para progenies de hiacutebridos con un par de caracteres diferenciantes) R y r su
proporcioacuten de la progenie seraacute de tres dominantes contra un recesivo
Cuando difieren en dos pares de caracteres la proporcioacuten seraacute de 9331
Redescubrimiento de las leyes de Mendel
En 1900 de manera independiente publicaron los resultados de sus trabajos haciendo referencia al trabajo ldquoprecursorrdquo de Mendel
bull El botaacutenico holandeacutes Hugo de Vries (1848-1935)
bull El botaacutenico alemaacuten Carl Correns (1864-1933)
bull El austriacuteaco Eric Tschermak von Seysenegg (1871-1962)
Este hecho marcoacute el inicio del estudio de la geneacutetica se extendieron y aplicaron los conocimientos mendelianos
bull Soacutelo Correns comprendioacute completamente el trabajo de Mendel y sus consecuencias Tanto De Vries como Tschermak no entendiacutean conceptos como dominancia y confundiacutean en una las dos leyes de Mendel en una sola Es entonces muy claro que el trabajo de Mendel no fue entendido ni en sus aspectos teacutecnicos ni tampoco en su importancia De hecho el entendimiento de su relevancia vino antes de ser entendido teacutecnicamente
Tomas H Morgan (1866-1945)
Teoriacutea cromosoacutemica de la herencia
Mapas cromosoacutemicos
Herencia ligada al sexo
Nobel 1933
El teacutermino biologiacutea molecular fue acuntildeado por el Director de la
Divisioacuten de Ciencias Naturales de la fundacioacuten Rokefeller Warren
Weaver en 1938
Warren Weaver
(1894-1978)Warren Weaver Hall
Washington
Hechos histoacutericos httpwwwnaturecomnaturejournalv422n6934pdftimeline_01626pdf
James Watson y Francis Crick
Premio Nobel 1962
1990 TICS Y BIOLOGIacuteA
La sociedad del conocimiento
bull Se refiere al incremento espectacular y a la aceleracioacuten sin precedente del ritmo de creacioacuten acumulacioacuten distribucioacuten y aprovechamiento de la informacioacuten y el conocimiento
-El conocimiento se crea se acumula se difunde y se aprovecha pues orienta las decisiones y permite la intervencioacuten en el mundo de acuerdo con ciertos fines y valores (Morales 2001)
bull El modelo de la Sociedad del Conocimiento estaacute en construccioacuten al igual que la sociedad misma (Oliveacute 2005)
(Re)evolucioacuten de la informacioacuten (1990)
bull Disentildeo de las computadoras
bull Aparicioacuten del Internet
bull Masificacioacuten de la web
bull Formato digital bajo costo poco espacio
bull Explosioacuten de la informacioacuten
bull Gran cantidad de colecciones de datos
bull Dinaacutemica cambia estaacute en modificacioacuten constante tanto el contenido como los formatos
bull Masiva
bull Aplicaciones de mata-anaacutelisis
(Re)evolucioacuten de la informacioacuten (cientiacutefica)bull La adopcioacuten del formato electroacutenico
bull Produccioacuten acelerada de una gran variedad de programas aplicaciones herramientas utilidades recursos y servicios electroacutenicos para la praacutectica cientiacutefica muchos de ellos disponibles a traveacutes de la Internet
bull Uso de la Web como medio de comunicacioacuten
bull El nuacutemero de los investigadores y de sus publicaciones se duplica aproximadamente cada veinte antildeos
bull Viven actualmente entre un 80 y un 90 de los cientiacuteficos que han existido
bull Se publican cada antildeo mas de dos millones de artiacuteculos
bull Se conceden un milloacuten de patentes
bull Modificacioacuten en la forma de producir evaluar y consultar la informacioacuten
ndash Revistas electroacutenicas
ndash Procedimiento electroacutenico
ndash Evaluacioacuten libre
ndash E-prints Preprints y posprints
ndash Inmediatez
bull Se han producido nuevas disciplinas cientiacuteficas
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
Comparacioacuten
Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
0
500
1000
1500
2000
2500
3000
1900
1905
1910
1915
1920
1925
1930
1935
1940
1945
1950
1955
1960
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1980
1985
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2005
Escherichia (94873)
Drosophila (48989)
Saccharomyces (27549)
Arabidopsis (18094)
Caenorhabditis (5353)
Year
Docu
men
ts
0
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100
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2005
Zea (7636)
Neurospora (6640)
Dictyostelium (6191)
Chlamydomonas (5646)
Schizosaccharomyces (3183)
Danio (973)
Year
Docu
men
tos
Figure 21
0
5
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Ge
ne
tics amp H
ere
dity
Bio
che
m amp
Mo
l Bio
Ce
ll Bio
De
velo
p B
io
Mu
ltidiscip
linary
Ne
uro
scien
ces
Bio
logy
Zoo
logy
Evolu
tion
ary Bio
Ecolo
gy
Ento
mo
logy
Toxico
logy
Ph
ysiolo
gy
Bio
ph
ysics
Bio
tech
amp M
icrob
io
Be
havio
ral Scien
Do
cum
en
ts
Subject Area
12581258 1231 1200 782 706
10907
8137
4310
2519 2482 2365 23401811
1465
6328
17900
(2)(1)
(20)
(3)
(15)
(18)
(6)
(3)(2)
Figure 22
0
100
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300
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1905
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Genetics amp Heredity
Biochemistry amp Molecular Biology
Cell Biology
Developmental Biology
Neuroscience
Year
Docu
men
ts
Figure 23
0
10
20
30
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19
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20
00
20
05
Evolutionary Biology
Ecology
Zoology
Toxicology
Year
Docu
men
ts
Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
0
100000
200000
300000
400000
500000
600000
700000
800000
1865
1870
1875
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1885
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1920
1925
1930
1935
1940
1945
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
500
1000
1500
2000
2500
3000
3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
100
200
300
400
500
600
Pu
blic
acio
ne
s
Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Historia de la cienciasEtapas
bull Antiguumledad (III ac V dc)
bull Edad Media(V-XIV)
bull Renacimiento (XV-XVI)
bull Etapa Moderna Temprana (XVII-XVIII)
bull Etapa Moderna (1800-1950)
bull Etapa Reciente o Contemporaacutenea(1950-2010)
Historia Biologiacutea (Problemas)
Historia Natural (in vivo)
ndash Siglo III AC-XIX
BiologiacuteaSiglo XX (in vitro)
Molecularizacioacuten
Siglo XXI (in silico)Computarizacioacuten
Los problemas de la Herencia Siglo XIX
bull La biologiacutea es una rama del conocimiento derivada de la siacutentesis de diversas tradiciones cientiacuteficas sin duda la maacutes importante es la Historia Natural pero durante el siglo XIX hubo otras quizaacutes menos abundantes en cuanto a produccioacuten pero igualmente relevantes en cuanto a las innovaciones conceptuales para la biologiacutea actual entre estas estaacuten
bull La herencia que estudiaba como se transmiten los caracteres de los padres a los hijos con base en
ndash La de los criadores y mejoradores enfocados al estudio del mejoramiento (especialmente de plantas) es decir en la herencia de los caracteres importantes para el hombre (agronomiacutea actual)
ndash La de los hibridoacutelogos encargados de estudiar la herencia de caracteres y la naturaleza de la especie (esencialista y nominalista) iniciada con Linneo
bull Habiacutea dos formas de estudiar la herencia de caracteres
ndash Los arboles genealoacutegicos o pedigriacutes
ndash Cruzas entre individuos con distintos caracteres
Gregor Mendel (1822-1884)bull En 1900 se redescubrioacute el trabajo de Gregor Mendel quien en 1865 habiacutea
anunciado el resultado de sus estudios con chiacutecharos ante la Sociedad
Bruniana
bull Los principales postulados de sus experimentos fueron
ndash Ciertos caracteres que pueden distinguirse faacutecilmente muestran
predominancia de unos sobre otros en la progenie de la cruza de padres
con caracteres opuestos o diferenciados
ndash Dos caracteres son transmitidos como elementos diferentes uno del padre
y otro de la madre en donde uno es dominante y el otro recesivo Los
caracteres que se transmiten y aparecen en la primera generacioacuten son los
dominantes y los que permanecen ocultos o de forma latente en el proceso
son los recesivos
bull Mendel usoacute la expresioacuten recesivo porque estos caracteres desaparecen en la
primera generacioacuten pero reaparecen en las subsecuentes
bull Reconocioacute que esos pares actuacutean independientemente de otros pares de
caracteres
bull De estos dos principios derivoacute algunas reglas aritmeacuteticas que rigen la herencia
Para progenies de hiacutebridos con un par de caracteres diferenciantes) R y r su
proporcioacuten de la progenie seraacute de tres dominantes contra un recesivo
Cuando difieren en dos pares de caracteres la proporcioacuten seraacute de 9331
Redescubrimiento de las leyes de Mendel
En 1900 de manera independiente publicaron los resultados de sus trabajos haciendo referencia al trabajo ldquoprecursorrdquo de Mendel
bull El botaacutenico holandeacutes Hugo de Vries (1848-1935)
bull El botaacutenico alemaacuten Carl Correns (1864-1933)
bull El austriacuteaco Eric Tschermak von Seysenegg (1871-1962)
Este hecho marcoacute el inicio del estudio de la geneacutetica se extendieron y aplicaron los conocimientos mendelianos
bull Soacutelo Correns comprendioacute completamente el trabajo de Mendel y sus consecuencias Tanto De Vries como Tschermak no entendiacutean conceptos como dominancia y confundiacutean en una las dos leyes de Mendel en una sola Es entonces muy claro que el trabajo de Mendel no fue entendido ni en sus aspectos teacutecnicos ni tampoco en su importancia De hecho el entendimiento de su relevancia vino antes de ser entendido teacutecnicamente
Tomas H Morgan (1866-1945)
Teoriacutea cromosoacutemica de la herencia
Mapas cromosoacutemicos
Herencia ligada al sexo
Nobel 1933
El teacutermino biologiacutea molecular fue acuntildeado por el Director de la
Divisioacuten de Ciencias Naturales de la fundacioacuten Rokefeller Warren
Weaver en 1938
Warren Weaver
(1894-1978)Warren Weaver Hall
Washington
Hechos histoacutericos httpwwwnaturecomnaturejournalv422n6934pdftimeline_01626pdf
James Watson y Francis Crick
Premio Nobel 1962
1990 TICS Y BIOLOGIacuteA
La sociedad del conocimiento
bull Se refiere al incremento espectacular y a la aceleracioacuten sin precedente del ritmo de creacioacuten acumulacioacuten distribucioacuten y aprovechamiento de la informacioacuten y el conocimiento
-El conocimiento se crea se acumula se difunde y se aprovecha pues orienta las decisiones y permite la intervencioacuten en el mundo de acuerdo con ciertos fines y valores (Morales 2001)
bull El modelo de la Sociedad del Conocimiento estaacute en construccioacuten al igual que la sociedad misma (Oliveacute 2005)
(Re)evolucioacuten de la informacioacuten (1990)
bull Disentildeo de las computadoras
bull Aparicioacuten del Internet
bull Masificacioacuten de la web
bull Formato digital bajo costo poco espacio
bull Explosioacuten de la informacioacuten
bull Gran cantidad de colecciones de datos
bull Dinaacutemica cambia estaacute en modificacioacuten constante tanto el contenido como los formatos
bull Masiva
bull Aplicaciones de mata-anaacutelisis
(Re)evolucioacuten de la informacioacuten (cientiacutefica)bull La adopcioacuten del formato electroacutenico
bull Produccioacuten acelerada de una gran variedad de programas aplicaciones herramientas utilidades recursos y servicios electroacutenicos para la praacutectica cientiacutefica muchos de ellos disponibles a traveacutes de la Internet
bull Uso de la Web como medio de comunicacioacuten
bull El nuacutemero de los investigadores y de sus publicaciones se duplica aproximadamente cada veinte antildeos
bull Viven actualmente entre un 80 y un 90 de los cientiacuteficos que han existido
bull Se publican cada antildeo mas de dos millones de artiacuteculos
bull Se conceden un milloacuten de patentes
bull Modificacioacuten en la forma de producir evaluar y consultar la informacioacuten
ndash Revistas electroacutenicas
ndash Procedimiento electroacutenico
ndash Evaluacioacuten libre
ndash E-prints Preprints y posprints
ndash Inmediatez
bull Se han producido nuevas disciplinas cientiacuteficas
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
Comparacioacuten
Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
0
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Escherichia (94873)
Drosophila (48989)
Saccharomyces (27549)
Arabidopsis (18094)
Caenorhabditis (5353)
Year
Docu
men
ts
0
50
100
150
200
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1900
1905
1910
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1935
1940
1945
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1965
1970
1975
1980
1985
1990
1995
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2005
Zea (7636)
Neurospora (6640)
Dictyostelium (6191)
Chlamydomonas (5646)
Schizosaccharomyces (3183)
Danio (973)
Year
Docu
men
tos
Figure 21
0
5
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Ge
ne
tics amp H
ere
dity
Bio
che
m amp
Mo
l Bio
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ll Bio
De
velo
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ltidiscip
linary
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uro
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Bio
logy
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logy
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tion
ary Bio
Ecolo
gy
Ento
mo
logy
Toxico
logy
Ph
ysiolo
gy
Bio
ph
ysics
Bio
tech
amp M
icrob
io
Be
havio
ral Scien
Do
cum
en
ts
Subject Area
12581258 1231 1200 782 706
10907
8137
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2519 2482 2365 23401811
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Figure 22
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
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1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
100
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blic
acio
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Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Historia Biologiacutea (Problemas)
Historia Natural (in vivo)
ndash Siglo III AC-XIX
BiologiacuteaSiglo XX (in vitro)
Molecularizacioacuten
Siglo XXI (in silico)Computarizacioacuten
Los problemas de la Herencia Siglo XIX
bull La biologiacutea es una rama del conocimiento derivada de la siacutentesis de diversas tradiciones cientiacuteficas sin duda la maacutes importante es la Historia Natural pero durante el siglo XIX hubo otras quizaacutes menos abundantes en cuanto a produccioacuten pero igualmente relevantes en cuanto a las innovaciones conceptuales para la biologiacutea actual entre estas estaacuten
bull La herencia que estudiaba como se transmiten los caracteres de los padres a los hijos con base en
ndash La de los criadores y mejoradores enfocados al estudio del mejoramiento (especialmente de plantas) es decir en la herencia de los caracteres importantes para el hombre (agronomiacutea actual)
ndash La de los hibridoacutelogos encargados de estudiar la herencia de caracteres y la naturaleza de la especie (esencialista y nominalista) iniciada con Linneo
bull Habiacutea dos formas de estudiar la herencia de caracteres
ndash Los arboles genealoacutegicos o pedigriacutes
ndash Cruzas entre individuos con distintos caracteres
Gregor Mendel (1822-1884)bull En 1900 se redescubrioacute el trabajo de Gregor Mendel quien en 1865 habiacutea
anunciado el resultado de sus estudios con chiacutecharos ante la Sociedad
Bruniana
bull Los principales postulados de sus experimentos fueron
ndash Ciertos caracteres que pueden distinguirse faacutecilmente muestran
predominancia de unos sobre otros en la progenie de la cruza de padres
con caracteres opuestos o diferenciados
ndash Dos caracteres son transmitidos como elementos diferentes uno del padre
y otro de la madre en donde uno es dominante y el otro recesivo Los
caracteres que se transmiten y aparecen en la primera generacioacuten son los
dominantes y los que permanecen ocultos o de forma latente en el proceso
son los recesivos
bull Mendel usoacute la expresioacuten recesivo porque estos caracteres desaparecen en la
primera generacioacuten pero reaparecen en las subsecuentes
bull Reconocioacute que esos pares actuacutean independientemente de otros pares de
caracteres
bull De estos dos principios derivoacute algunas reglas aritmeacuteticas que rigen la herencia
Para progenies de hiacutebridos con un par de caracteres diferenciantes) R y r su
proporcioacuten de la progenie seraacute de tres dominantes contra un recesivo
Cuando difieren en dos pares de caracteres la proporcioacuten seraacute de 9331
Redescubrimiento de las leyes de Mendel
En 1900 de manera independiente publicaron los resultados de sus trabajos haciendo referencia al trabajo ldquoprecursorrdquo de Mendel
bull El botaacutenico holandeacutes Hugo de Vries (1848-1935)
bull El botaacutenico alemaacuten Carl Correns (1864-1933)
bull El austriacuteaco Eric Tschermak von Seysenegg (1871-1962)
Este hecho marcoacute el inicio del estudio de la geneacutetica se extendieron y aplicaron los conocimientos mendelianos
bull Soacutelo Correns comprendioacute completamente el trabajo de Mendel y sus consecuencias Tanto De Vries como Tschermak no entendiacutean conceptos como dominancia y confundiacutean en una las dos leyes de Mendel en una sola Es entonces muy claro que el trabajo de Mendel no fue entendido ni en sus aspectos teacutecnicos ni tampoco en su importancia De hecho el entendimiento de su relevancia vino antes de ser entendido teacutecnicamente
Tomas H Morgan (1866-1945)
Teoriacutea cromosoacutemica de la herencia
Mapas cromosoacutemicos
Herencia ligada al sexo
Nobel 1933
El teacutermino biologiacutea molecular fue acuntildeado por el Director de la
Divisioacuten de Ciencias Naturales de la fundacioacuten Rokefeller Warren
Weaver en 1938
Warren Weaver
(1894-1978)Warren Weaver Hall
Washington
Hechos histoacutericos httpwwwnaturecomnaturejournalv422n6934pdftimeline_01626pdf
James Watson y Francis Crick
Premio Nobel 1962
1990 TICS Y BIOLOGIacuteA
La sociedad del conocimiento
bull Se refiere al incremento espectacular y a la aceleracioacuten sin precedente del ritmo de creacioacuten acumulacioacuten distribucioacuten y aprovechamiento de la informacioacuten y el conocimiento
-El conocimiento se crea se acumula se difunde y se aprovecha pues orienta las decisiones y permite la intervencioacuten en el mundo de acuerdo con ciertos fines y valores (Morales 2001)
bull El modelo de la Sociedad del Conocimiento estaacute en construccioacuten al igual que la sociedad misma (Oliveacute 2005)
(Re)evolucioacuten de la informacioacuten (1990)
bull Disentildeo de las computadoras
bull Aparicioacuten del Internet
bull Masificacioacuten de la web
bull Formato digital bajo costo poco espacio
bull Explosioacuten de la informacioacuten
bull Gran cantidad de colecciones de datos
bull Dinaacutemica cambia estaacute en modificacioacuten constante tanto el contenido como los formatos
bull Masiva
bull Aplicaciones de mata-anaacutelisis
(Re)evolucioacuten de la informacioacuten (cientiacutefica)bull La adopcioacuten del formato electroacutenico
bull Produccioacuten acelerada de una gran variedad de programas aplicaciones herramientas utilidades recursos y servicios electroacutenicos para la praacutectica cientiacutefica muchos de ellos disponibles a traveacutes de la Internet
bull Uso de la Web como medio de comunicacioacuten
bull El nuacutemero de los investigadores y de sus publicaciones se duplica aproximadamente cada veinte antildeos
bull Viven actualmente entre un 80 y un 90 de los cientiacuteficos que han existido
bull Se publican cada antildeo mas de dos millones de artiacuteculos
bull Se conceden un milloacuten de patentes
bull Modificacioacuten en la forma de producir evaluar y consultar la informacioacuten
ndash Revistas electroacutenicas
ndash Procedimiento electroacutenico
ndash Evaluacioacuten libre
ndash E-prints Preprints y posprints
ndash Inmediatez
bull Se han producido nuevas disciplinas cientiacuteficas
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
Comparacioacuten
Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
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500
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3000
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1925
1930
1935
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1945
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1955
1960
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1970
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1980
1985
1990
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2000
2005
Escherichia (94873)
Drosophila (48989)
Saccharomyces (27549)
Arabidopsis (18094)
Caenorhabditis (5353)
Year
Docu
men
ts
0
50
100
150
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1975
1980
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2000
2005
Zea (7636)
Neurospora (6640)
Dictyostelium (6191)
Chlamydomonas (5646)
Schizosaccharomyces (3183)
Danio (973)
Year
Docu
men
tos
Figure 21
0
5
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Ge
ne
tics amp H
ere
dity
Bio
che
m amp
Mo
l Bio
Ce
ll Bio
De
velo
p B
io
Mu
ltidiscip
linary
Ne
uro
scien
ces
Bio
logy
Zoo
logy
Evolu
tion
ary Bio
Ecolo
gy
Ento
mo
logy
Toxico
logy
Ph
ysiolo
gy
Bio
ph
ysics
Bio
tech
amp M
icrob
io
Be
havio
ral Scien
Do
cum
en
ts
Subject Area
12581258 1231 1200 782 706
10907
8137
4310
2519 2482 2365 23401811
1465
6328
17900
(2)(1)
(20)
(3)
(15)
(18)
(6)
(3)(2)
Figure 22
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Genetics amp Heredity
Biochemistry amp Molecular Biology
Cell Biology
Developmental Biology
Neuroscience
Year
Docu
men
ts
Figure 23
0
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40
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95
20
00
20
05
Evolutionary Biology
Ecology
Zoology
Toxicology
Year
Docu
men
ts
Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
0
100000
200000
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1995
2000
2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
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3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
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blic
acio
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Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Los problemas de la Herencia Siglo XIX
bull La biologiacutea es una rama del conocimiento derivada de la siacutentesis de diversas tradiciones cientiacuteficas sin duda la maacutes importante es la Historia Natural pero durante el siglo XIX hubo otras quizaacutes menos abundantes en cuanto a produccioacuten pero igualmente relevantes en cuanto a las innovaciones conceptuales para la biologiacutea actual entre estas estaacuten
bull La herencia que estudiaba como se transmiten los caracteres de los padres a los hijos con base en
ndash La de los criadores y mejoradores enfocados al estudio del mejoramiento (especialmente de plantas) es decir en la herencia de los caracteres importantes para el hombre (agronomiacutea actual)
ndash La de los hibridoacutelogos encargados de estudiar la herencia de caracteres y la naturaleza de la especie (esencialista y nominalista) iniciada con Linneo
bull Habiacutea dos formas de estudiar la herencia de caracteres
ndash Los arboles genealoacutegicos o pedigriacutes
ndash Cruzas entre individuos con distintos caracteres
Gregor Mendel (1822-1884)bull En 1900 se redescubrioacute el trabajo de Gregor Mendel quien en 1865 habiacutea
anunciado el resultado de sus estudios con chiacutecharos ante la Sociedad
Bruniana
bull Los principales postulados de sus experimentos fueron
ndash Ciertos caracteres que pueden distinguirse faacutecilmente muestran
predominancia de unos sobre otros en la progenie de la cruza de padres
con caracteres opuestos o diferenciados
ndash Dos caracteres son transmitidos como elementos diferentes uno del padre
y otro de la madre en donde uno es dominante y el otro recesivo Los
caracteres que se transmiten y aparecen en la primera generacioacuten son los
dominantes y los que permanecen ocultos o de forma latente en el proceso
son los recesivos
bull Mendel usoacute la expresioacuten recesivo porque estos caracteres desaparecen en la
primera generacioacuten pero reaparecen en las subsecuentes
bull Reconocioacute que esos pares actuacutean independientemente de otros pares de
caracteres
bull De estos dos principios derivoacute algunas reglas aritmeacuteticas que rigen la herencia
Para progenies de hiacutebridos con un par de caracteres diferenciantes) R y r su
proporcioacuten de la progenie seraacute de tres dominantes contra un recesivo
Cuando difieren en dos pares de caracteres la proporcioacuten seraacute de 9331
Redescubrimiento de las leyes de Mendel
En 1900 de manera independiente publicaron los resultados de sus trabajos haciendo referencia al trabajo ldquoprecursorrdquo de Mendel
bull El botaacutenico holandeacutes Hugo de Vries (1848-1935)
bull El botaacutenico alemaacuten Carl Correns (1864-1933)
bull El austriacuteaco Eric Tschermak von Seysenegg (1871-1962)
Este hecho marcoacute el inicio del estudio de la geneacutetica se extendieron y aplicaron los conocimientos mendelianos
bull Soacutelo Correns comprendioacute completamente el trabajo de Mendel y sus consecuencias Tanto De Vries como Tschermak no entendiacutean conceptos como dominancia y confundiacutean en una las dos leyes de Mendel en una sola Es entonces muy claro que el trabajo de Mendel no fue entendido ni en sus aspectos teacutecnicos ni tampoco en su importancia De hecho el entendimiento de su relevancia vino antes de ser entendido teacutecnicamente
Tomas H Morgan (1866-1945)
Teoriacutea cromosoacutemica de la herencia
Mapas cromosoacutemicos
Herencia ligada al sexo
Nobel 1933
El teacutermino biologiacutea molecular fue acuntildeado por el Director de la
Divisioacuten de Ciencias Naturales de la fundacioacuten Rokefeller Warren
Weaver en 1938
Warren Weaver
(1894-1978)Warren Weaver Hall
Washington
Hechos histoacutericos httpwwwnaturecomnaturejournalv422n6934pdftimeline_01626pdf
James Watson y Francis Crick
Premio Nobel 1962
1990 TICS Y BIOLOGIacuteA
La sociedad del conocimiento
bull Se refiere al incremento espectacular y a la aceleracioacuten sin precedente del ritmo de creacioacuten acumulacioacuten distribucioacuten y aprovechamiento de la informacioacuten y el conocimiento
-El conocimiento se crea se acumula se difunde y se aprovecha pues orienta las decisiones y permite la intervencioacuten en el mundo de acuerdo con ciertos fines y valores (Morales 2001)
bull El modelo de la Sociedad del Conocimiento estaacute en construccioacuten al igual que la sociedad misma (Oliveacute 2005)
(Re)evolucioacuten de la informacioacuten (1990)
bull Disentildeo de las computadoras
bull Aparicioacuten del Internet
bull Masificacioacuten de la web
bull Formato digital bajo costo poco espacio
bull Explosioacuten de la informacioacuten
bull Gran cantidad de colecciones de datos
bull Dinaacutemica cambia estaacute en modificacioacuten constante tanto el contenido como los formatos
bull Masiva
bull Aplicaciones de mata-anaacutelisis
(Re)evolucioacuten de la informacioacuten (cientiacutefica)bull La adopcioacuten del formato electroacutenico
bull Produccioacuten acelerada de una gran variedad de programas aplicaciones herramientas utilidades recursos y servicios electroacutenicos para la praacutectica cientiacutefica muchos de ellos disponibles a traveacutes de la Internet
bull Uso de la Web como medio de comunicacioacuten
bull El nuacutemero de los investigadores y de sus publicaciones se duplica aproximadamente cada veinte antildeos
bull Viven actualmente entre un 80 y un 90 de los cientiacuteficos que han existido
bull Se publican cada antildeo mas de dos millones de artiacuteculos
bull Se conceden un milloacuten de patentes
bull Modificacioacuten en la forma de producir evaluar y consultar la informacioacuten
ndash Revistas electroacutenicas
ndash Procedimiento electroacutenico
ndash Evaluacioacuten libre
ndash E-prints Preprints y posprints
ndash Inmediatez
bull Se han producido nuevas disciplinas cientiacuteficas
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
Comparacioacuten
Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
0
500
1000
1500
2000
2500
3000
1900
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1920
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1930
1935
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1955
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Escherichia (94873)
Drosophila (48989)
Saccharomyces (27549)
Arabidopsis (18094)
Caenorhabditis (5353)
Year
Docu
men
ts
0
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100
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2000
2005
Zea (7636)
Neurospora (6640)
Dictyostelium (6191)
Chlamydomonas (5646)
Schizosaccharomyces (3183)
Danio (973)
Year
Docu
men
tos
Figure 21
0
5
10
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20
25
30
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40
Ge
ne
tics amp H
ere
dity
Bio
che
m amp
Mo
l Bio
Ce
ll Bio
De
velo
p B
io
Mu
ltidiscip
linary
Ne
uro
scien
ces
Bio
logy
Zoo
logy
Evolu
tion
ary Bio
Ecolo
gy
Ento
mo
logy
Toxico
logy
Ph
ysiolo
gy
Bio
ph
ysics
Bio
tech
amp M
icrob
io
Be
havio
ral Scien
Do
cum
en
ts
Subject Area
12581258 1231 1200 782 706
10907
8137
4310
2519 2482 2365 23401811
1465
6328
17900
(2)(1)
(20)
(3)
(15)
(18)
(6)
(3)(2)
Figure 22
0
100
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1905
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Genetics amp Heredity
Biochemistry amp Molecular Biology
Cell Biology
Developmental Biology
Neuroscience
Year
Docu
men
ts
Figure 23
0
10
20
30
40
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19
05
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95
20
00
20
05
Evolutionary Biology
Ecology
Zoology
Toxicology
Year
Docu
men
ts
Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
0
100000
200000
300000
400000
500000
600000
700000
800000
1865
1870
1875
1880
1885
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1920
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1930
1935
1940
1945
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
500
1000
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3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
100
200
300
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500
600
Pu
blic
acio
ne
s
Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Gregor Mendel (1822-1884)bull En 1900 se redescubrioacute el trabajo de Gregor Mendel quien en 1865 habiacutea
anunciado el resultado de sus estudios con chiacutecharos ante la Sociedad
Bruniana
bull Los principales postulados de sus experimentos fueron
ndash Ciertos caracteres que pueden distinguirse faacutecilmente muestran
predominancia de unos sobre otros en la progenie de la cruza de padres
con caracteres opuestos o diferenciados
ndash Dos caracteres son transmitidos como elementos diferentes uno del padre
y otro de la madre en donde uno es dominante y el otro recesivo Los
caracteres que se transmiten y aparecen en la primera generacioacuten son los
dominantes y los que permanecen ocultos o de forma latente en el proceso
son los recesivos
bull Mendel usoacute la expresioacuten recesivo porque estos caracteres desaparecen en la
primera generacioacuten pero reaparecen en las subsecuentes
bull Reconocioacute que esos pares actuacutean independientemente de otros pares de
caracteres
bull De estos dos principios derivoacute algunas reglas aritmeacuteticas que rigen la herencia
Para progenies de hiacutebridos con un par de caracteres diferenciantes) R y r su
proporcioacuten de la progenie seraacute de tres dominantes contra un recesivo
Cuando difieren en dos pares de caracteres la proporcioacuten seraacute de 9331
Redescubrimiento de las leyes de Mendel
En 1900 de manera independiente publicaron los resultados de sus trabajos haciendo referencia al trabajo ldquoprecursorrdquo de Mendel
bull El botaacutenico holandeacutes Hugo de Vries (1848-1935)
bull El botaacutenico alemaacuten Carl Correns (1864-1933)
bull El austriacuteaco Eric Tschermak von Seysenegg (1871-1962)
Este hecho marcoacute el inicio del estudio de la geneacutetica se extendieron y aplicaron los conocimientos mendelianos
bull Soacutelo Correns comprendioacute completamente el trabajo de Mendel y sus consecuencias Tanto De Vries como Tschermak no entendiacutean conceptos como dominancia y confundiacutean en una las dos leyes de Mendel en una sola Es entonces muy claro que el trabajo de Mendel no fue entendido ni en sus aspectos teacutecnicos ni tampoco en su importancia De hecho el entendimiento de su relevancia vino antes de ser entendido teacutecnicamente
Tomas H Morgan (1866-1945)
Teoriacutea cromosoacutemica de la herencia
Mapas cromosoacutemicos
Herencia ligada al sexo
Nobel 1933
El teacutermino biologiacutea molecular fue acuntildeado por el Director de la
Divisioacuten de Ciencias Naturales de la fundacioacuten Rokefeller Warren
Weaver en 1938
Warren Weaver
(1894-1978)Warren Weaver Hall
Washington
Hechos histoacutericos httpwwwnaturecomnaturejournalv422n6934pdftimeline_01626pdf
James Watson y Francis Crick
Premio Nobel 1962
1990 TICS Y BIOLOGIacuteA
La sociedad del conocimiento
bull Se refiere al incremento espectacular y a la aceleracioacuten sin precedente del ritmo de creacioacuten acumulacioacuten distribucioacuten y aprovechamiento de la informacioacuten y el conocimiento
-El conocimiento se crea se acumula se difunde y se aprovecha pues orienta las decisiones y permite la intervencioacuten en el mundo de acuerdo con ciertos fines y valores (Morales 2001)
bull El modelo de la Sociedad del Conocimiento estaacute en construccioacuten al igual que la sociedad misma (Oliveacute 2005)
(Re)evolucioacuten de la informacioacuten (1990)
bull Disentildeo de las computadoras
bull Aparicioacuten del Internet
bull Masificacioacuten de la web
bull Formato digital bajo costo poco espacio
bull Explosioacuten de la informacioacuten
bull Gran cantidad de colecciones de datos
bull Dinaacutemica cambia estaacute en modificacioacuten constante tanto el contenido como los formatos
bull Masiva
bull Aplicaciones de mata-anaacutelisis
(Re)evolucioacuten de la informacioacuten (cientiacutefica)bull La adopcioacuten del formato electroacutenico
bull Produccioacuten acelerada de una gran variedad de programas aplicaciones herramientas utilidades recursos y servicios electroacutenicos para la praacutectica cientiacutefica muchos de ellos disponibles a traveacutes de la Internet
bull Uso de la Web como medio de comunicacioacuten
bull El nuacutemero de los investigadores y de sus publicaciones se duplica aproximadamente cada veinte antildeos
bull Viven actualmente entre un 80 y un 90 de los cientiacuteficos que han existido
bull Se publican cada antildeo mas de dos millones de artiacuteculos
bull Se conceden un milloacuten de patentes
bull Modificacioacuten en la forma de producir evaluar y consultar la informacioacuten
ndash Revistas electroacutenicas
ndash Procedimiento electroacutenico
ndash Evaluacioacuten libre
ndash E-prints Preprints y posprints
ndash Inmediatez
bull Se han producido nuevas disciplinas cientiacuteficas
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
Comparacioacuten
Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
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500
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1900
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Escherichia (94873)
Drosophila (48989)
Saccharomyces (27549)
Arabidopsis (18094)
Caenorhabditis (5353)
Year
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men
ts
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Zea (7636)
Neurospora (6640)
Dictyostelium (6191)
Chlamydomonas (5646)
Schizosaccharomyces (3183)
Danio (973)
Year
Docu
men
tos
Figure 21
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Ge
ne
tics amp H
ere
dity
Bio
che
m amp
Mo
l Bio
Ce
ll Bio
De
velo
p B
io
Mu
ltidiscip
linary
Ne
uro
scien
ces
Bio
logy
Zoo
logy
Evolu
tion
ary Bio
Ecolo
gy
Ento
mo
logy
Toxico
logy
Ph
ysiolo
gy
Bio
ph
ysics
Bio
tech
amp M
icrob
io
Be
havio
ral Scien
Do
cum
en
ts
Subject Area
12581258 1231 1200 782 706
10907
8137
4310
2519 2482 2365 23401811
1465
6328
17900
(2)(1)
(20)
(3)
(15)
(18)
(6)
(3)(2)
Figure 22
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Genetics amp Heredity
Biochemistry amp Molecular Biology
Cell Biology
Developmental Biology
Neuroscience
Year
Docu
men
ts
Figure 23
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Evolutionary Biology
Ecology
Zoology
Toxicology
Year
Docu
men
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
0
100000
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1990
1995
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2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
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1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
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600
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blic
acio
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Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Para progenies de hiacutebridos con un par de caracteres diferenciantes) R y r su
proporcioacuten de la progenie seraacute de tres dominantes contra un recesivo
Cuando difieren en dos pares de caracteres la proporcioacuten seraacute de 9331
Redescubrimiento de las leyes de Mendel
En 1900 de manera independiente publicaron los resultados de sus trabajos haciendo referencia al trabajo ldquoprecursorrdquo de Mendel
bull El botaacutenico holandeacutes Hugo de Vries (1848-1935)
bull El botaacutenico alemaacuten Carl Correns (1864-1933)
bull El austriacuteaco Eric Tschermak von Seysenegg (1871-1962)
Este hecho marcoacute el inicio del estudio de la geneacutetica se extendieron y aplicaron los conocimientos mendelianos
bull Soacutelo Correns comprendioacute completamente el trabajo de Mendel y sus consecuencias Tanto De Vries como Tschermak no entendiacutean conceptos como dominancia y confundiacutean en una las dos leyes de Mendel en una sola Es entonces muy claro que el trabajo de Mendel no fue entendido ni en sus aspectos teacutecnicos ni tampoco en su importancia De hecho el entendimiento de su relevancia vino antes de ser entendido teacutecnicamente
Tomas H Morgan (1866-1945)
Teoriacutea cromosoacutemica de la herencia
Mapas cromosoacutemicos
Herencia ligada al sexo
Nobel 1933
El teacutermino biologiacutea molecular fue acuntildeado por el Director de la
Divisioacuten de Ciencias Naturales de la fundacioacuten Rokefeller Warren
Weaver en 1938
Warren Weaver
(1894-1978)Warren Weaver Hall
Washington
Hechos histoacutericos httpwwwnaturecomnaturejournalv422n6934pdftimeline_01626pdf
James Watson y Francis Crick
Premio Nobel 1962
1990 TICS Y BIOLOGIacuteA
La sociedad del conocimiento
bull Se refiere al incremento espectacular y a la aceleracioacuten sin precedente del ritmo de creacioacuten acumulacioacuten distribucioacuten y aprovechamiento de la informacioacuten y el conocimiento
-El conocimiento se crea se acumula se difunde y se aprovecha pues orienta las decisiones y permite la intervencioacuten en el mundo de acuerdo con ciertos fines y valores (Morales 2001)
bull El modelo de la Sociedad del Conocimiento estaacute en construccioacuten al igual que la sociedad misma (Oliveacute 2005)
(Re)evolucioacuten de la informacioacuten (1990)
bull Disentildeo de las computadoras
bull Aparicioacuten del Internet
bull Masificacioacuten de la web
bull Formato digital bajo costo poco espacio
bull Explosioacuten de la informacioacuten
bull Gran cantidad de colecciones de datos
bull Dinaacutemica cambia estaacute en modificacioacuten constante tanto el contenido como los formatos
bull Masiva
bull Aplicaciones de mata-anaacutelisis
(Re)evolucioacuten de la informacioacuten (cientiacutefica)bull La adopcioacuten del formato electroacutenico
bull Produccioacuten acelerada de una gran variedad de programas aplicaciones herramientas utilidades recursos y servicios electroacutenicos para la praacutectica cientiacutefica muchos de ellos disponibles a traveacutes de la Internet
bull Uso de la Web como medio de comunicacioacuten
bull El nuacutemero de los investigadores y de sus publicaciones se duplica aproximadamente cada veinte antildeos
bull Viven actualmente entre un 80 y un 90 de los cientiacuteficos que han existido
bull Se publican cada antildeo mas de dos millones de artiacuteculos
bull Se conceden un milloacuten de patentes
bull Modificacioacuten en la forma de producir evaluar y consultar la informacioacuten
ndash Revistas electroacutenicas
ndash Procedimiento electroacutenico
ndash Evaluacioacuten libre
ndash E-prints Preprints y posprints
ndash Inmediatez
bull Se han producido nuevas disciplinas cientiacuteficas
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
Comparacioacuten
Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
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1970
1975
1980
1985
1990
1995
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2005
Escherichia (94873)
Drosophila (48989)
Saccharomyces (27549)
Arabidopsis (18094)
Caenorhabditis (5353)
Year
Docu
men
ts
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2005
Zea (7636)
Neurospora (6640)
Dictyostelium (6191)
Chlamydomonas (5646)
Schizosaccharomyces (3183)
Danio (973)
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men
tos
Figure 21
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uro
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logy
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tion
ary Bio
Ecolo
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mo
logy
Toxico
logy
Ph
ysiolo
gy
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ph
ysics
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tech
amp M
icrob
io
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havio
ral Scien
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cum
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Subject Area
12581258 1231 1200 782 706
10907
8137
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2519 2482 2365 23401811
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6328
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(6)
(3)(2)
Figure 22
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Genetics amp Heredity
Biochemistry amp Molecular Biology
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Figure 23
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Ecology
Zoology
Toxicology
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
500
1000
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3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
100
200
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500
600
Pu
blic
acio
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Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Redescubrimiento de las leyes de Mendel
En 1900 de manera independiente publicaron los resultados de sus trabajos haciendo referencia al trabajo ldquoprecursorrdquo de Mendel
bull El botaacutenico holandeacutes Hugo de Vries (1848-1935)
bull El botaacutenico alemaacuten Carl Correns (1864-1933)
bull El austriacuteaco Eric Tschermak von Seysenegg (1871-1962)
Este hecho marcoacute el inicio del estudio de la geneacutetica se extendieron y aplicaron los conocimientos mendelianos
bull Soacutelo Correns comprendioacute completamente el trabajo de Mendel y sus consecuencias Tanto De Vries como Tschermak no entendiacutean conceptos como dominancia y confundiacutean en una las dos leyes de Mendel en una sola Es entonces muy claro que el trabajo de Mendel no fue entendido ni en sus aspectos teacutecnicos ni tampoco en su importancia De hecho el entendimiento de su relevancia vino antes de ser entendido teacutecnicamente
Tomas H Morgan (1866-1945)
Teoriacutea cromosoacutemica de la herencia
Mapas cromosoacutemicos
Herencia ligada al sexo
Nobel 1933
El teacutermino biologiacutea molecular fue acuntildeado por el Director de la
Divisioacuten de Ciencias Naturales de la fundacioacuten Rokefeller Warren
Weaver en 1938
Warren Weaver
(1894-1978)Warren Weaver Hall
Washington
Hechos histoacutericos httpwwwnaturecomnaturejournalv422n6934pdftimeline_01626pdf
James Watson y Francis Crick
Premio Nobel 1962
1990 TICS Y BIOLOGIacuteA
La sociedad del conocimiento
bull Se refiere al incremento espectacular y a la aceleracioacuten sin precedente del ritmo de creacioacuten acumulacioacuten distribucioacuten y aprovechamiento de la informacioacuten y el conocimiento
-El conocimiento se crea se acumula se difunde y se aprovecha pues orienta las decisiones y permite la intervencioacuten en el mundo de acuerdo con ciertos fines y valores (Morales 2001)
bull El modelo de la Sociedad del Conocimiento estaacute en construccioacuten al igual que la sociedad misma (Oliveacute 2005)
(Re)evolucioacuten de la informacioacuten (1990)
bull Disentildeo de las computadoras
bull Aparicioacuten del Internet
bull Masificacioacuten de la web
bull Formato digital bajo costo poco espacio
bull Explosioacuten de la informacioacuten
bull Gran cantidad de colecciones de datos
bull Dinaacutemica cambia estaacute en modificacioacuten constante tanto el contenido como los formatos
bull Masiva
bull Aplicaciones de mata-anaacutelisis
(Re)evolucioacuten de la informacioacuten (cientiacutefica)bull La adopcioacuten del formato electroacutenico
bull Produccioacuten acelerada de una gran variedad de programas aplicaciones herramientas utilidades recursos y servicios electroacutenicos para la praacutectica cientiacutefica muchos de ellos disponibles a traveacutes de la Internet
bull Uso de la Web como medio de comunicacioacuten
bull El nuacutemero de los investigadores y de sus publicaciones se duplica aproximadamente cada veinte antildeos
bull Viven actualmente entre un 80 y un 90 de los cientiacuteficos que han existido
bull Se publican cada antildeo mas de dos millones de artiacuteculos
bull Se conceden un milloacuten de patentes
bull Modificacioacuten en la forma de producir evaluar y consultar la informacioacuten
ndash Revistas electroacutenicas
ndash Procedimiento electroacutenico
ndash Evaluacioacuten libre
ndash E-prints Preprints y posprints
ndash Inmediatez
bull Se han producido nuevas disciplinas cientiacuteficas
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
Comparacioacuten
Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
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io
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linary
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logy
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ysics
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tech
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12581258 1231 1200 782 706
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Figure 22
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Ecology
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
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1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
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Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Tomas H Morgan (1866-1945)
Teoriacutea cromosoacutemica de la herencia
Mapas cromosoacutemicos
Herencia ligada al sexo
Nobel 1933
El teacutermino biologiacutea molecular fue acuntildeado por el Director de la
Divisioacuten de Ciencias Naturales de la fundacioacuten Rokefeller Warren
Weaver en 1938
Warren Weaver
(1894-1978)Warren Weaver Hall
Washington
Hechos histoacutericos httpwwwnaturecomnaturejournalv422n6934pdftimeline_01626pdf
James Watson y Francis Crick
Premio Nobel 1962
1990 TICS Y BIOLOGIacuteA
La sociedad del conocimiento
bull Se refiere al incremento espectacular y a la aceleracioacuten sin precedente del ritmo de creacioacuten acumulacioacuten distribucioacuten y aprovechamiento de la informacioacuten y el conocimiento
-El conocimiento se crea se acumula se difunde y se aprovecha pues orienta las decisiones y permite la intervencioacuten en el mundo de acuerdo con ciertos fines y valores (Morales 2001)
bull El modelo de la Sociedad del Conocimiento estaacute en construccioacuten al igual que la sociedad misma (Oliveacute 2005)
(Re)evolucioacuten de la informacioacuten (1990)
bull Disentildeo de las computadoras
bull Aparicioacuten del Internet
bull Masificacioacuten de la web
bull Formato digital bajo costo poco espacio
bull Explosioacuten de la informacioacuten
bull Gran cantidad de colecciones de datos
bull Dinaacutemica cambia estaacute en modificacioacuten constante tanto el contenido como los formatos
bull Masiva
bull Aplicaciones de mata-anaacutelisis
(Re)evolucioacuten de la informacioacuten (cientiacutefica)bull La adopcioacuten del formato electroacutenico
bull Produccioacuten acelerada de una gran variedad de programas aplicaciones herramientas utilidades recursos y servicios electroacutenicos para la praacutectica cientiacutefica muchos de ellos disponibles a traveacutes de la Internet
bull Uso de la Web como medio de comunicacioacuten
bull El nuacutemero de los investigadores y de sus publicaciones se duplica aproximadamente cada veinte antildeos
bull Viven actualmente entre un 80 y un 90 de los cientiacuteficos que han existido
bull Se publican cada antildeo mas de dos millones de artiacuteculos
bull Se conceden un milloacuten de patentes
bull Modificacioacuten en la forma de producir evaluar y consultar la informacioacuten
ndash Revistas electroacutenicas
ndash Procedimiento electroacutenico
ndash Evaluacioacuten libre
ndash E-prints Preprints y posprints
ndash Inmediatez
bull Se han producido nuevas disciplinas cientiacuteficas
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
Comparacioacuten
Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
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Escherichia (94873)
Drosophila (48989)
Saccharomyces (27549)
Arabidopsis (18094)
Caenorhabditis (5353)
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men
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Zea (7636)
Neurospora (6640)
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Chlamydomonas (5646)
Schizosaccharomyces (3183)
Danio (973)
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men
tos
Figure 21
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Ge
ne
tics amp H
ere
dity
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che
m amp
Mo
l Bio
Ce
ll Bio
De
velo
p B
io
Mu
ltidiscip
linary
Ne
uro
scien
ces
Bio
logy
Zoo
logy
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tion
ary Bio
Ecolo
gy
Ento
mo
logy
Toxico
logy
Ph
ysiolo
gy
Bio
ph
ysics
Bio
tech
amp M
icrob
io
Be
havio
ral Scien
Do
cum
en
ts
Subject Area
12581258 1231 1200 782 706
10907
8137
4310
2519 2482 2365 23401811
1465
6328
17900
(2)(1)
(20)
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Figure 22
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Genetics amp Heredity
Biochemistry amp Molecular Biology
Cell Biology
Developmental Biology
Neuroscience
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men
ts
Figure 23
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Evolutionary Biology
Ecology
Zoology
Toxicology
Year
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men
ts
Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
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1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
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blic
acio
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Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
El teacutermino biologiacutea molecular fue acuntildeado por el Director de la
Divisioacuten de Ciencias Naturales de la fundacioacuten Rokefeller Warren
Weaver en 1938
Warren Weaver
(1894-1978)Warren Weaver Hall
Washington
Hechos histoacutericos httpwwwnaturecomnaturejournalv422n6934pdftimeline_01626pdf
James Watson y Francis Crick
Premio Nobel 1962
1990 TICS Y BIOLOGIacuteA
La sociedad del conocimiento
bull Se refiere al incremento espectacular y a la aceleracioacuten sin precedente del ritmo de creacioacuten acumulacioacuten distribucioacuten y aprovechamiento de la informacioacuten y el conocimiento
-El conocimiento se crea se acumula se difunde y se aprovecha pues orienta las decisiones y permite la intervencioacuten en el mundo de acuerdo con ciertos fines y valores (Morales 2001)
bull El modelo de la Sociedad del Conocimiento estaacute en construccioacuten al igual que la sociedad misma (Oliveacute 2005)
(Re)evolucioacuten de la informacioacuten (1990)
bull Disentildeo de las computadoras
bull Aparicioacuten del Internet
bull Masificacioacuten de la web
bull Formato digital bajo costo poco espacio
bull Explosioacuten de la informacioacuten
bull Gran cantidad de colecciones de datos
bull Dinaacutemica cambia estaacute en modificacioacuten constante tanto el contenido como los formatos
bull Masiva
bull Aplicaciones de mata-anaacutelisis
(Re)evolucioacuten de la informacioacuten (cientiacutefica)bull La adopcioacuten del formato electroacutenico
bull Produccioacuten acelerada de una gran variedad de programas aplicaciones herramientas utilidades recursos y servicios electroacutenicos para la praacutectica cientiacutefica muchos de ellos disponibles a traveacutes de la Internet
bull Uso de la Web como medio de comunicacioacuten
bull El nuacutemero de los investigadores y de sus publicaciones se duplica aproximadamente cada veinte antildeos
bull Viven actualmente entre un 80 y un 90 de los cientiacuteficos que han existido
bull Se publican cada antildeo mas de dos millones de artiacuteculos
bull Se conceden un milloacuten de patentes
bull Modificacioacuten en la forma de producir evaluar y consultar la informacioacuten
ndash Revistas electroacutenicas
ndash Procedimiento electroacutenico
ndash Evaluacioacuten libre
ndash E-prints Preprints y posprints
ndash Inmediatez
bull Se han producido nuevas disciplinas cientiacuteficas
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
Comparacioacuten
Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
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Escherichia (94873)
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Arabidopsis (18094)
Caenorhabditis (5353)
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Danio (973)
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men
tos
Figure 21
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Ge
ne
tics amp H
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che
m amp
Mo
l Bio
Ce
ll Bio
De
velo
p B
io
Mu
ltidiscip
linary
Ne
uro
scien
ces
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logy
Zoo
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tion
ary Bio
Ecolo
gy
Ento
mo
logy
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logy
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ysiolo
gy
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ph
ysics
Bio
tech
amp M
icrob
io
Be
havio
ral Scien
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cum
en
ts
Subject Area
12581258 1231 1200 782 706
10907
8137
4310
2519 2482 2365 23401811
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Figure 22
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Figure 23
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
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1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
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blic
acio
ne
s
Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Hechos histoacutericos httpwwwnaturecomnaturejournalv422n6934pdftimeline_01626pdf
James Watson y Francis Crick
Premio Nobel 1962
1990 TICS Y BIOLOGIacuteA
La sociedad del conocimiento
bull Se refiere al incremento espectacular y a la aceleracioacuten sin precedente del ritmo de creacioacuten acumulacioacuten distribucioacuten y aprovechamiento de la informacioacuten y el conocimiento
-El conocimiento se crea se acumula se difunde y se aprovecha pues orienta las decisiones y permite la intervencioacuten en el mundo de acuerdo con ciertos fines y valores (Morales 2001)
bull El modelo de la Sociedad del Conocimiento estaacute en construccioacuten al igual que la sociedad misma (Oliveacute 2005)
(Re)evolucioacuten de la informacioacuten (1990)
bull Disentildeo de las computadoras
bull Aparicioacuten del Internet
bull Masificacioacuten de la web
bull Formato digital bajo costo poco espacio
bull Explosioacuten de la informacioacuten
bull Gran cantidad de colecciones de datos
bull Dinaacutemica cambia estaacute en modificacioacuten constante tanto el contenido como los formatos
bull Masiva
bull Aplicaciones de mata-anaacutelisis
(Re)evolucioacuten de la informacioacuten (cientiacutefica)bull La adopcioacuten del formato electroacutenico
bull Produccioacuten acelerada de una gran variedad de programas aplicaciones herramientas utilidades recursos y servicios electroacutenicos para la praacutectica cientiacutefica muchos de ellos disponibles a traveacutes de la Internet
bull Uso de la Web como medio de comunicacioacuten
bull El nuacutemero de los investigadores y de sus publicaciones se duplica aproximadamente cada veinte antildeos
bull Viven actualmente entre un 80 y un 90 de los cientiacuteficos que han existido
bull Se publican cada antildeo mas de dos millones de artiacuteculos
bull Se conceden un milloacuten de patentes
bull Modificacioacuten en la forma de producir evaluar y consultar la informacioacuten
ndash Revistas electroacutenicas
ndash Procedimiento electroacutenico
ndash Evaluacioacuten libre
ndash E-prints Preprints y posprints
ndash Inmediatez
bull Se han producido nuevas disciplinas cientiacuteficas
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
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Schizosaccharomyces (3183)
Danio (973)
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men
tos
Figure 21
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velo
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io
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ltidiscip
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uro
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logy
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logy
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ysiolo
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ph
ysics
Bio
tech
amp M
icrob
io
Be
havio
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Subject Area
12581258 1231 1200 782 706
10907
8137
4310
2519 2482 2365 23401811
1465
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17900
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Figure 22
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Genetics amp Heredity
Biochemistry amp Molecular Biology
Cell Biology
Developmental Biology
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men
ts
Figure 23
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Evolutionary Biology
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
0
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
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1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
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Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
James Watson y Francis Crick
Premio Nobel 1962
1990 TICS Y BIOLOGIacuteA
La sociedad del conocimiento
bull Se refiere al incremento espectacular y a la aceleracioacuten sin precedente del ritmo de creacioacuten acumulacioacuten distribucioacuten y aprovechamiento de la informacioacuten y el conocimiento
-El conocimiento se crea se acumula se difunde y se aprovecha pues orienta las decisiones y permite la intervencioacuten en el mundo de acuerdo con ciertos fines y valores (Morales 2001)
bull El modelo de la Sociedad del Conocimiento estaacute en construccioacuten al igual que la sociedad misma (Oliveacute 2005)
(Re)evolucioacuten de la informacioacuten (1990)
bull Disentildeo de las computadoras
bull Aparicioacuten del Internet
bull Masificacioacuten de la web
bull Formato digital bajo costo poco espacio
bull Explosioacuten de la informacioacuten
bull Gran cantidad de colecciones de datos
bull Dinaacutemica cambia estaacute en modificacioacuten constante tanto el contenido como los formatos
bull Masiva
bull Aplicaciones de mata-anaacutelisis
(Re)evolucioacuten de la informacioacuten (cientiacutefica)bull La adopcioacuten del formato electroacutenico
bull Produccioacuten acelerada de una gran variedad de programas aplicaciones herramientas utilidades recursos y servicios electroacutenicos para la praacutectica cientiacutefica muchos de ellos disponibles a traveacutes de la Internet
bull Uso de la Web como medio de comunicacioacuten
bull El nuacutemero de los investigadores y de sus publicaciones se duplica aproximadamente cada veinte antildeos
bull Viven actualmente entre un 80 y un 90 de los cientiacuteficos que han existido
bull Se publican cada antildeo mas de dos millones de artiacuteculos
bull Se conceden un milloacuten de patentes
bull Modificacioacuten en la forma de producir evaluar y consultar la informacioacuten
ndash Revistas electroacutenicas
ndash Procedimiento electroacutenico
ndash Evaluacioacuten libre
ndash E-prints Preprints y posprints
ndash Inmediatez
bull Se han producido nuevas disciplinas cientiacuteficas
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
Comparacioacuten
Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
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Escherichia (94873)
Drosophila (48989)
Saccharomyces (27549)
Arabidopsis (18094)
Caenorhabditis (5353)
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Zea (7636)
Neurospora (6640)
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Schizosaccharomyces (3183)
Danio (973)
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men
tos
Figure 21
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Ge
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velo
p B
io
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ltidiscip
linary
Ne
uro
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logy
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ary Bio
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mo
logy
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gy
Bio
ph
ysics
Bio
tech
amp M
icrob
io
Be
havio
ral Scien
Do
cum
en
ts
Subject Area
12581258 1231 1200 782 706
10907
8137
4310
2519 2482 2365 23401811
1465
6328
17900
(2)(1)
(20)
(3)
(15)
(18)
(6)
(3)(2)
Figure 22
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Genetics amp Heredity
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Cell Biology
Developmental Biology
Neuroscience
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men
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Figure 23
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
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1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
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Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
1990 TICS Y BIOLOGIacuteA
La sociedad del conocimiento
bull Se refiere al incremento espectacular y a la aceleracioacuten sin precedente del ritmo de creacioacuten acumulacioacuten distribucioacuten y aprovechamiento de la informacioacuten y el conocimiento
-El conocimiento se crea se acumula se difunde y se aprovecha pues orienta las decisiones y permite la intervencioacuten en el mundo de acuerdo con ciertos fines y valores (Morales 2001)
bull El modelo de la Sociedad del Conocimiento estaacute en construccioacuten al igual que la sociedad misma (Oliveacute 2005)
(Re)evolucioacuten de la informacioacuten (1990)
bull Disentildeo de las computadoras
bull Aparicioacuten del Internet
bull Masificacioacuten de la web
bull Formato digital bajo costo poco espacio
bull Explosioacuten de la informacioacuten
bull Gran cantidad de colecciones de datos
bull Dinaacutemica cambia estaacute en modificacioacuten constante tanto el contenido como los formatos
bull Masiva
bull Aplicaciones de mata-anaacutelisis
(Re)evolucioacuten de la informacioacuten (cientiacutefica)bull La adopcioacuten del formato electroacutenico
bull Produccioacuten acelerada de una gran variedad de programas aplicaciones herramientas utilidades recursos y servicios electroacutenicos para la praacutectica cientiacutefica muchos de ellos disponibles a traveacutes de la Internet
bull Uso de la Web como medio de comunicacioacuten
bull El nuacutemero de los investigadores y de sus publicaciones se duplica aproximadamente cada veinte antildeos
bull Viven actualmente entre un 80 y un 90 de los cientiacuteficos que han existido
bull Se publican cada antildeo mas de dos millones de artiacuteculos
bull Se conceden un milloacuten de patentes
bull Modificacioacuten en la forma de producir evaluar y consultar la informacioacuten
ndash Revistas electroacutenicas
ndash Procedimiento electroacutenico
ndash Evaluacioacuten libre
ndash E-prints Preprints y posprints
ndash Inmediatez
bull Se han producido nuevas disciplinas cientiacuteficas
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
Comparacioacuten
Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
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Escherichia (94873)
Drosophila (48989)
Saccharomyces (27549)
Arabidopsis (18094)
Caenorhabditis (5353)
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Figure 21
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logy
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logy
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tech
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Be
havio
ral Scien
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Subject Area
12581258 1231 1200 782 706
10907
8137
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2519 2482 2365 23401811
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Figure 22
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Figure 23
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
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3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
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blic
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Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
La sociedad del conocimiento
bull Se refiere al incremento espectacular y a la aceleracioacuten sin precedente del ritmo de creacioacuten acumulacioacuten distribucioacuten y aprovechamiento de la informacioacuten y el conocimiento
-El conocimiento se crea se acumula se difunde y se aprovecha pues orienta las decisiones y permite la intervencioacuten en el mundo de acuerdo con ciertos fines y valores (Morales 2001)
bull El modelo de la Sociedad del Conocimiento estaacute en construccioacuten al igual que la sociedad misma (Oliveacute 2005)
(Re)evolucioacuten de la informacioacuten (1990)
bull Disentildeo de las computadoras
bull Aparicioacuten del Internet
bull Masificacioacuten de la web
bull Formato digital bajo costo poco espacio
bull Explosioacuten de la informacioacuten
bull Gran cantidad de colecciones de datos
bull Dinaacutemica cambia estaacute en modificacioacuten constante tanto el contenido como los formatos
bull Masiva
bull Aplicaciones de mata-anaacutelisis
(Re)evolucioacuten de la informacioacuten (cientiacutefica)bull La adopcioacuten del formato electroacutenico
bull Produccioacuten acelerada de una gran variedad de programas aplicaciones herramientas utilidades recursos y servicios electroacutenicos para la praacutectica cientiacutefica muchos de ellos disponibles a traveacutes de la Internet
bull Uso de la Web como medio de comunicacioacuten
bull El nuacutemero de los investigadores y de sus publicaciones se duplica aproximadamente cada veinte antildeos
bull Viven actualmente entre un 80 y un 90 de los cientiacuteficos que han existido
bull Se publican cada antildeo mas de dos millones de artiacuteculos
bull Se conceden un milloacuten de patentes
bull Modificacioacuten en la forma de producir evaluar y consultar la informacioacuten
ndash Revistas electroacutenicas
ndash Procedimiento electroacutenico
ndash Evaluacioacuten libre
ndash E-prints Preprints y posprints
ndash Inmediatez
bull Se han producido nuevas disciplinas cientiacuteficas
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
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Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
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Figure 21
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logy
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ysics
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tech
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12581258 1231 1200 782 706
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Figure 22
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Figure 23
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Evolutionary Biology
Ecology
Zoology
Toxicology
Year
Docu
men
ts
Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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1980
1985
1990
1995
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2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
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1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
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blic
acio
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Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
(Re)evolucioacuten de la informacioacuten (1990)
bull Disentildeo de las computadoras
bull Aparicioacuten del Internet
bull Masificacioacuten de la web
bull Formato digital bajo costo poco espacio
bull Explosioacuten de la informacioacuten
bull Gran cantidad de colecciones de datos
bull Dinaacutemica cambia estaacute en modificacioacuten constante tanto el contenido como los formatos
bull Masiva
bull Aplicaciones de mata-anaacutelisis
(Re)evolucioacuten de la informacioacuten (cientiacutefica)bull La adopcioacuten del formato electroacutenico
bull Produccioacuten acelerada de una gran variedad de programas aplicaciones herramientas utilidades recursos y servicios electroacutenicos para la praacutectica cientiacutefica muchos de ellos disponibles a traveacutes de la Internet
bull Uso de la Web como medio de comunicacioacuten
bull El nuacutemero de los investigadores y de sus publicaciones se duplica aproximadamente cada veinte antildeos
bull Viven actualmente entre un 80 y un 90 de los cientiacuteficos que han existido
bull Se publican cada antildeo mas de dos millones de artiacuteculos
bull Se conceden un milloacuten de patentes
bull Modificacioacuten en la forma de producir evaluar y consultar la informacioacuten
ndash Revistas electroacutenicas
ndash Procedimiento electroacutenico
ndash Evaluacioacuten libre
ndash E-prints Preprints y posprints
ndash Inmediatez
bull Se han producido nuevas disciplinas cientiacuteficas
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
Comparacioacuten
Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
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Escherichia (94873)
Drosophila (48989)
Saccharomyces (27549)
Arabidopsis (18094)
Caenorhabditis (5353)
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Zea (7636)
Neurospora (6640)
Dictyostelium (6191)
Chlamydomonas (5646)
Schizosaccharomyces (3183)
Danio (973)
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Figure 21
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Ge
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tics amp H
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dity
Bio
che
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De
velo
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io
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ltidiscip
linary
Ne
uro
scien
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Bio
logy
Zoo
logy
Evolu
tion
ary Bio
Ecolo
gy
Ento
mo
logy
Toxico
logy
Ph
ysiolo
gy
Bio
ph
ysics
Bio
tech
amp M
icrob
io
Be
havio
ral Scien
Do
cum
en
ts
Subject Area
12581258 1231 1200 782 706
10907
8137
4310
2519 2482 2365 23401811
1465
6328
17900
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(20)
(3)
(15)
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(6)
(3)(2)
Figure 22
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Figure 23
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
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1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
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blic
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Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
(Re)evolucioacuten de la informacioacuten (cientiacutefica)bull La adopcioacuten del formato electroacutenico
bull Produccioacuten acelerada de una gran variedad de programas aplicaciones herramientas utilidades recursos y servicios electroacutenicos para la praacutectica cientiacutefica muchos de ellos disponibles a traveacutes de la Internet
bull Uso de la Web como medio de comunicacioacuten
bull El nuacutemero de los investigadores y de sus publicaciones se duplica aproximadamente cada veinte antildeos
bull Viven actualmente entre un 80 y un 90 de los cientiacuteficos que han existido
bull Se publican cada antildeo mas de dos millones de artiacuteculos
bull Se conceden un milloacuten de patentes
bull Modificacioacuten en la forma de producir evaluar y consultar la informacioacuten
ndash Revistas electroacutenicas
ndash Procedimiento electroacutenico
ndash Evaluacioacuten libre
ndash E-prints Preprints y posprints
ndash Inmediatez
bull Se han producido nuevas disciplinas cientiacuteficas
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
Comparacioacuten
Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
0
500
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Figure 21
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De
velo
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io
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ltidiscip
linary
Ne
uro
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Bio
logy
Zoo
logy
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tion
ary Bio
Ecolo
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Ento
mo
logy
Toxico
logy
Ph
ysiolo
gy
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ph
ysics
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tech
amp M
icrob
io
Be
havio
ral Scien
Do
cum
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Subject Area
12581258 1231 1200 782 706
10907
8137
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2519 2482 2365 23401811
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Figure 22
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Genetics amp Heredity
Biochemistry amp Molecular Biology
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Developmental Biology
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Figure 23
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Ecology
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
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3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
100
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500
600
Pu
blic
acio
ne
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Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
La transformacioacuten de la biologiacutea
bull Molecularizacioacutenbull Colaboracioacutenbull Multidisciplinariedadbull Proyectos internacionalesbull Gridsbull Nuevos modelosbull Nuevas disciplinas
ndash Bioinformaacuteticandash Informaacutetica Meacutedicandash Neuroinformaacuteticandash Biologiacutea de Sistemas
bull Colecciones de datosndash Bioloacutegicasndash Bibliograacuteficas
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
Comparacioacuten
Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
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Escherichia (94873)
Drosophila (48989)
Saccharomyces (27549)
Arabidopsis (18094)
Caenorhabditis (5353)
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Neurospora (6640)
Dictyostelium (6191)
Chlamydomonas (5646)
Schizosaccharomyces (3183)
Danio (973)
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Figure 21
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che
m amp
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l Bio
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ll Bio
De
velo
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io
Mu
ltidiscip
linary
Ne
uro
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Bio
logy
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tion
ary Bio
Ecolo
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mo
logy
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logy
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ysiolo
gy
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ph
ysics
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tech
amp M
icrob
io
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havio
ral Scien
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cum
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Subject Area
12581258 1231 1200 782 706
10907
8137
4310
2519 2482 2365 23401811
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Figure 22
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Genetics amp Heredity
Biochemistry amp Molecular Biology
Cell Biology
Developmental Biology
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Figure 23
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Ecology
Zoology
Toxicology
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men
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
500
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3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
100
200
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500
600
Pu
blic
acio
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s
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Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Investigacioacuten bioloacutegica
Observacioacuten
Descripcioacuten
ClasificacioacutenExperimentacioacuten
Comparacioacuten
Investigacioacuten Cientiacutefica(Biologiacutea)
In vivoIn vitro (1900)In Silico (1990)
0
500
1000
1500
2000
2500
3000
1900
1905
1910
1915
1920
1925
1930
1935
1940
1945
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
Escherichia (94873)
Drosophila (48989)
Saccharomyces (27549)
Arabidopsis (18094)
Caenorhabditis (5353)
Year
Docu
men
ts
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Zea (7636)
Neurospora (6640)
Dictyostelium (6191)
Chlamydomonas (5646)
Schizosaccharomyces (3183)
Danio (973)
Year
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men
tos
Figure 21
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De
velo
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linary
Ne
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Bio
logy
Zoo
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tion
ary Bio
Ecolo
gy
Ento
mo
logy
Toxico
logy
Ph
ysiolo
gy
Bio
ph
ysics
Bio
tech
amp M
icrob
io
Be
havio
ral Scien
Do
cum
en
ts
Subject Area
12581258 1231 1200 782 706
10907
8137
4310
2519 2482 2365 23401811
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(2)(1)
(20)
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(6)
(3)(2)
Figure 22
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Genetics amp Heredity
Biochemistry amp Molecular Biology
Cell Biology
Developmental Biology
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Figure 23
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Ecology
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
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1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
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Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
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1970
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1985
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Escherichia (94873)
Drosophila (48989)
Saccharomyces (27549)
Arabidopsis (18094)
Caenorhabditis (5353)
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Docu
men
ts
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2005
Zea (7636)
Neurospora (6640)
Dictyostelium (6191)
Chlamydomonas (5646)
Schizosaccharomyces (3183)
Danio (973)
Year
Docu
men
tos
Figure 21
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Bio
logy
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logy
Evolu
tion
ary Bio
Ecolo
gy
Ento
mo
logy
Toxico
logy
Ph
ysiolo
gy
Bio
ph
ysics
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tech
amp M
icrob
io
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havio
ral Scien
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cum
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Subject Area
12581258 1231 1200 782 706
10907
8137
4310
2519 2482 2365 23401811
1465
6328
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(2)(1)
(20)
(3)
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(6)
(3)(2)
Figure 22
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Genetics amp Heredity
Biochemistry amp Molecular Biology
Cell Biology
Developmental Biology
Neuroscience
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Figure 23
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Ecology
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
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blic
acio
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s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
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Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
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1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
Zea (7636)
Neurospora (6640)
Dictyostelium (6191)
Chlamydomonas (5646)
Schizosaccharomyces (3183)
Danio (973)
Year
Docu
men
tos
Figure 21
0
5
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15
20
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Ge
ne
tics amp H
ere
dity
Bio
che
m amp
Mo
l Bio
Ce
ll Bio
De
velo
p B
io
Mu
ltidiscip
linary
Ne
uro
scien
ces
Bio
logy
Zoo
logy
Evolu
tion
ary Bio
Ecolo
gy
Ento
mo
logy
Toxico
logy
Ph
ysiolo
gy
Bio
ph
ysics
Bio
tech
amp M
icrob
io
Be
havio
ral Scien
Do
cum
en
ts
Subject Area
12581258 1231 1200 782 706
10907
8137
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2519 2482 2365 23401811
1465
6328
17900
(2)(1)
(20)
(3)
(15)
(18)
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Figure 22
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
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blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
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Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Figure 21
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Ge
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che
m amp
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l Bio
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ll Bio
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velo
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io
Mu
ltidiscip
linary
Ne
uro
scien
ces
Bio
logy
Zoo
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Evolu
tion
ary Bio
Ecolo
gy
Ento
mo
logy
Toxico
logy
Ph
ysiolo
gy
Bio
ph
ysics
Bio
tech
amp M
icrob
io
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havio
ral Scien
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cum
en
ts
Subject Area
12581258 1231 1200 782 706
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Figure 22
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Genetics amp Heredity
Biochemistry amp Molecular Biology
Cell Biology
Developmental Biology
Neuroscience
Year
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Figure 23
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Ecology
Zoology
Toxicology
Year
Docu
men
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
0
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1960
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1970
1975
1980
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1990
1995
2000
2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
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Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
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Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Figure 22
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Biochemistry amp Molecular Biology
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Figure 23
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Ecology
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Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
0
100000
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1940
1945
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
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1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
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blic
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Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Figure 23
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Evolutionary Biology
Ecology
Zoology
Toxicology
Year
Docu
men
ts
Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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100000
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1980
1985
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2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
500
1000
1500
2000
2500
3000
3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
100
200
300
400
500
600
Pu
blic
acio
ne
s
Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Coleccioacuten de
secuencias de
genesE-ciencia
Ciberinfraestructura
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
0
100000
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800000
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1925
1930
1935
1940
1945
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
500
1000
1500
2000
2500
3000
3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
100
200
300
400
500
600
Pu
blic
acio
ne
s
Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Genbank
bull Es una coleccioacuten anotada de todas las secuencias de nucleoacutetidos a disposicioacuten del puacuteblico y su traduccioacuten de proteiacutenas
bull Centro Nacional de Informacioacuten Biotecnoloacutegica (NCBI)bull European Molecular Biology Laboratory (EMBL) de datos de
Bibliotecas del Instituto Europeo de Bioinformaacutetica (EBI)bull DNA Data Bank de Japoacuten (DDBJ)bull Reciben las secuencias producidas en laboratorios de todo el
mundo de maacutes de 100000 organismos distintosbull Crece a un ritmo exponencial duplicando cada 10 meses Suelte
134 producido en febrero de 2003 conteniacutea maacutes de 29300 millones de bases nucleotiacutedicas en maacutes de 230 millones de secuencias
bull Se construye mediante el enviacuteo directo de los distintos laboratorios y de los centros de secuenciacioacuten a gran escala
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
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1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
100
200
300
400
500
600
Pu
blic
acio
ne
s
Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
httpwwwncbinlmnihgovgenbankgenbankstatshtml
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
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1945
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1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
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Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
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blic
acio
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Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Olson M Hood L Cantor C Botstein D A common language for physical mapping of the human genome Science 1989 245(4925) 1434ndash1435 [PubMed]
0
100000
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1940
1945
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
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1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
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Pu
blic
acio
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Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
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1975
1980
1985
1990
1995
2000
2005
Documentos en PubMed (NIH)
Cerca de 20 millones octubre 2010)
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
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Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
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blic
acio
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Institucioacuten
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Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
e-science cyberinfraestructure
bull e-science (europe)
bull United Kingdoms Office of Science and Technology in 1999
bull Will refer to the large scale science that will increasingly be carried out through distributed global collaborations enabled by the Internet
bull cyberinfraestructure (USA)bull United States National Science
Foundation (NSF) blue-ribbon committee in 2003
bull Describes the new research environments that support advanced data acquisition data storage data management data integration data mining data visualization and other computing and information processing services over the Internet
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
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3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
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600
Pu
blic
acio
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Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Ciberinfraestructura
bullEntorno tecnoloacutegico-social que permite crear difundir y preservar los datos informacioacuten y conocimientos mediante la adquisicioacuten almacenamiento gestioacuten integracioacuten informaacutetica mineriacutea visualizacioacuten y otros servicios a traveacutes de Internet (NSF 2003 2007)
bullIncluye un conjunto interoperable de diversos elementos
ndash1) Infraestructura los sistemas computacionales (hardware software y redes) servicios instrumentos y herramientas
ndash2) Colecciones de datos
ndash3) Grupos virtuales de investigacioacuten (colaboratorios y observatorios)
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
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2000
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3000
3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
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600
Pu
blic
acio
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s
Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
e-investigacioacutenbull Actividades de investigacioacuten que utilizan una gama de capacidades avanzadas de las TIC y abarca
nuevas metodologiacuteas de investigacioacuten que salen de un mayor acceso a
Las comunicaciones de banda ancha de redes instrumentos de investigacioacuten y las instalaciones redes de sensores y repositorios de datos
Software y servicios de infraestructura que permitan garantizar la conectividad e interoperabilidad
Aplicacioacuten herramientas que abarcan la disciplina de instrumentos especiacuteficos y herramientas de interaccioacuten
avanzar y aumentar en lugar de reemplazar las tradicionales metodologiacuteas de investigacioacuten
bull permitiraacute a los investigadores para llevar a cabo su labor de investigacioacuten maacutes creativa eficiente y colaboracioacuten a larga distancia y difundir sus resultados de la investigacioacuten con un mayor efecto
bull Colaboracioacuten
Nuevos campos de investigacioacuten emergentes utilizando nuevas teacutecnicas de mineriacutea de datos y el anaacutelisis avanzados algoritmos computacionales y de redes de intercambio de recursos
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
500
1000
1500
2000
2500
3000
3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
100
200
300
400
500
600
Pu
blic
acio
ne
s
Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
e-Science bull Originally referred to experiments that connected together a few powerful
computers located at different sites and later a very large number of modest PCs across the world in order to undertake enormous calculations or process huge amounts of data The coordination of geographically dispersed computing and data resources has become known as the Grid This is shorthand for the emerging standards and technology ndash hardware and software ndash being developed to enable and simplify the sharing of resources The analogy is an electric power grid which comprises numerous varied resources connected together to contribute power into a shared pool that users can easily access when they need it
bull What is exciting about the Grid is that the combination of extensive connectivity massive computer power and vast quantities of digitized data ndash all three of which are still rapidly expanding ndash making possible new applications that are orders of magnitude more potent than even a few years ago
bull The term e-research is sometimes used instead of e-science with the advantage that gives more emphasis to the end result of better richer faster or new research results rather than the technologies used to get them
National Centre for e-Social Science 2008 Frequently Asked Questions Diponible en httpwwwncessacukabout_eSSfaqq=General_1General_1
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
500
1000
1500
2000
2500
3000
3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
100
200
300
400
500
600
Pu
blic
acio
ne
s
Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
E-ciencia (e-science)
bull Resulta del uso y aplicacioacuten de la Ciberinfraestructura en la praacutectica cientifica
bull Se caracteriza por la inter y multidisciplinariedad
bull Colaboracioacuten la participacioacuten de un gran nuacutemero de investigadores (en algunos casos cientos) localizados en diversas regiones y con diferentes especialidades que se forman grupos trabajo (Hey y Trefethen 2005 Barbera et al2009)
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
500
1000
1500
2000
2500
3000
3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
100
200
300
400
500
600
Pu
blic
acio
ne
s
Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Uno de los primeros proyectos de e-ciencia fue el de el genoma humano se publicoacute en el 2001 en dos artiacuteculos con un diacutea de diferencia en las revistas Nature y Science
NatureInitial sequencing and analysis of the human genome79 Autores48 Instituciones
181 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientesDepartment of Cellular and Structural BiologyDepartment of Molecular GeneticsDepartment of Molecular Biology
Science The Sequence of the Human Genome276 Autores14 Instituciones452 referenciasTodos los autores provenientes de departamentos de Ciencias Genoacutemicas (o geneacutetica) exceptuando los siguientes Department of Biology e Informaacutetica Meacutedica
E-ciencia
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
500
1000
1500
2000
2500
3000
3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
100
200
300
400
500
600
Pu
blic
acio
ne
s
Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
1865 Gregor Mendel descubre las leyes de la Geneacutetica httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1953 James Watson y Francis Crick describen la estructura de la doble-heacutelice del ADN httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1966 Marshall Nirenberg Har Gobind Khorana y Robert Holley determinan el coacutedigo
geneacutetico
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1972 Stanley Cohen and Herbert Boyer desarrollan la tecnologiacutea del ADN recombinante httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1977 Frederick Sanger Allan Maxam y Walter Gilbert desarrollan meacutetodos de
secuenciacioacuten del ADN
httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1982 La base de datos bdquoGenBank‟ es establecida httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1985 Es inventada la Reaccioacuten en Cadena de la Polimerasa (PCR) httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1990 El Proyecto Genoma Humano (HGP) inicia en Estados Unidos httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
1997 El genoma de Escherichia coli es secuenciado httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
2003 La secuencia del genoma humano es finalizada httpwwwnaturecomnaturejournalv42
2n6934pdf timeline_01626pdf
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
500
1000
1500
2000
2500
3000
3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
100
200
300
400
500
600
Pu
blic
acio
ne
s
Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
La Genoacutemicabull Es el estudio sistemaacutetico de la documentacioacuten completa de
las secuencias del ADN de los organismos (MeSH 2010) dicho estudio ha ayudado a comprender polimorfismos dentro de las especies la interaccioacuten de las proteiacutenas y la evolucioacuten (Brent 2000)
bull Incluye todos los meacutetodos que recopilan y analizan datos completos acerca de los genes incluida las secuencias la abundancia de los aacutecidos nucleicos y las propiedades de las proteiacutenas que codifican (Murray 2000)
bull Nuestra capacidad para estudiar la funcioacuten geacutenica estaacute aumentando en la especificidad gracias a esta nueva disciplina (Collins et aacutel 2003) que se compromete a acelerar el descubrimiento cientiacutefico en todos los aacutembitos de la ciencia bioloacutegica (Burley 2000)
0
500
1000
1500
2000
2500
3000
3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
100
200
300
400
500
600
Pu
blic
acio
ne
s
Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
0
500
1000
1500
2000
2500
3000
3500
1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009
Pu
blic
acio
ne
s
Antildeo
Nuacutemero de Publicaciones
Pathology and
immunopathology
research en 1988 The
genomics of human
homeobox-containing
loci‟ escrito por CA
Ferguson-Smith y FH
Ruddle del
Departamento de
Biologiacutea en la
Universidad de Yale
New Haven
Connecticut
0
100
200
300
400
500
600
Pu
blic
acio
ne
s
Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
0
100
200
300
400
500
600
Pu
blic
acio
ne
s
Institucioacuten
Nuacutemero de Publicaciones
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Nature 2001 Feb 15409(6822)860-921Initial sequencing and analysis of the human genome
Lander ES Linton LM Birren B Nusbaum C Zody MC Baldwin J Devon K Dewar K Doyle M FitzHugh W Funke R GageD Harris K Heaford A Howland J Kann L Lehoczky J LeVine R McEwan P McKernan K Meldrim J Mesirov JP Miranda C Morris W Naylor J Raymond C Rosetti M Santos R Sheridan A Sougnez C Stange-Thomann NStojanovicN Subramanian A Wyman D Rogers J Sulston J Ainscough R Beck S Bentley D Burton J Clee C Carter N CoulsonA Deadman R Deloukas P Dunham ADunham I Durbin R French L Grafham D Gregory S Hubbard T HumphrayS Hunt A Jones M Lloyd C McMurray A Matthews L Mercer S Milne S Mullikin JC Mungall APlumb R Ross M Shownkeen R Sims S Waterston RH Wilson RK Hillier LW McPherson JD Marra MA Mardis ER FultonLA Chinwalla AT Pepin KH Gish WR Chissoe SL Wendl MC Delehaunty KD Miner TL Delehaunty A Kramer JB Cook LL Fulton RS Johnson DL Minx PJ Clifton SW Hawkins T Branscomb E Predki P Richardson PWenning S SlezakT Doggett N Cheng JF Olsen A Lucas S Elkin C Uberbacher E Frazier M Gibbs RA Muzny DM Scherer SE BouckJB Sodergren EJ Worley KC Rives CM Gorrell JH Metzker ML Naylor SL Kucherlapati RS Nelson DL WeinstockGM Sakaki Y Fujiyama A Hattori M Yada T Toyoda A Itoh T Kawagoe C Watanabe H Totoki YTaylor T WeissenbachJ Heilig R Saurin W Artiguenave F Brottier P Bruls T Pelletier E Robert C Wincker P Smith DR Doucette-StammL Rubenfield M Weinstock K Lee HM Dubois J Rosenthal A Platzer M Nyakatura G Taudien S Rump A Yang H YuJ Wang J Huang G Gu J Hood L Rowen L Madan A Qin S Davis RW Federspiel NAAbola AP Proctor MJ Myers RM Schmutz J Dickson M Grimwood J Cox DR Olson MV Kaul R Raymond C Shimizu N Kawasaki K MinoshimaS Evans GA Athanasiou MSchultz R Roe BA Chen F Pan H Ramser J Lehrach H Reinhardt R McCombie WR de la Bastide M Dedhia N Bloumlcker H Hornischer K Nordsiek G Agarwala R Aravind LBailey JA Bateman A BatzoglouS Birney E Bork P Brown DG Burge CB Cerutti L Chen HC Church D Clamp M Copley RR Doerks T Eddy SR EichlerEE Furey TSGalagan J Gilbert JG Harmon C Hayashizaki Y Haussler D Hermjakob H Hokamp K Jang W Johnson LS Jones TA Kasif S Kaspryzk A Kennedy S Kent WJ Kitts PKoonin EV Korf I Kulp D Lancet D Lowe TM McLysaghtA Mikkelsen T Moran JV Mulder N Pollara VJ Ponting CP Schuler G Schultz J Slater G Smit AF Stupka ESzustakowskiJ Thierry-Mieg D Thierry-Mieg J Wagner L Wallis J Wheeler R Williams A Wolf YI Wolfe KH Yang SP Yeh RF Collins F Guyer MS Peterson J Felsenfeld AWetterstrand KA Patrinos A Morgan MJ de Jong P Catanese JJ OsoegawaK Shizuya H Choi S Chen YJ International Human Genome Sequencing Consortium
Whitehead Institute for Biomedical Research Center for Genome Research Cambridge Massachusetts 02142 USA landergenomewimitedu
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
bull The human genome holds an extraordinary trove of information about human development physiology medicine and evolution Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome We also present an initial analysis of the data describing some of the insights that can be gleaned from the sequence
bull Here we report the results of a collaboration involving 20 groups from the United States the United Kingdom Japan France Germany and China to produce a draft sequence of the human genome
bull Of course navigating information spanning nearly ten orders of magnitude requires computational tools to extract the full value
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
FIGURA 1 Liacutenea de tiempo de los anaacutelisis genoacutemicos a gran escala
Nature 409 860-921(15 February 2001)doi10103835057062
httpwwwnaturecomnaturejournalv409n6822fig_tab409860a0_F1html
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Nature 409 860-921(15 February 2001)doi10103835057062httpwwwnaturecomnaturejournalv409n6822images409860ac2jpg
FIGURE 3 The automated production line for sample preparation at the Whitehead Institute Center for Genome Research
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
bull Science 16 February 2001Vol 291 no 5507 pp 1304 - 1351DOI 101126science1058040
bull REVIEW
bull The Sequence of the Human Genome
bull J Craig Venter1 Mark D Adams1 Eugene W Myers1 Peter W Li1 Richard J Mural1 Granger G Sutton1 Hamilton O Smith1 Mark Yandell1 Cheryl A Evans1Robert A Holt1 Jeannine D Gocayne1 Peter Amanatides1 Richard M Ballew1 Daniel H Huson1 Jennifer Russo Wortman1 Qing Zhang1Chinnappa D Kodira1 Xiangqun H Zheng1 Lin Chen1 Marian Skupski1 Gangadharan Subramanian1 Paul D Thomas1 Jinghui Zhang1George L Gabor Miklos2 Catherine Nelson3 Samuel Broder1 Andrew G Clark4 Joe Nadeau5 Victor A McKusick6 Norton Zinder7 Arnold J Levine7Richard J Roberts8 MelSimon9 Carolyn Slayman10 Michael Hunkapiller11 Randall Bolanos1 Arthur Delcher1 Ian Dew1 Daniel Fasulo1 Michael Flanigan1Liliana Florea1 Aaron Halpern1 Sridhar Hannenhalli1 Saul Kravitz1 Samuel Levy1 Clark Mobarry1 KnutReinert1 Karin Remington1 Jane Abu-Threideh1Ellen Beasley1 Kendra Biddick1 Vivien Bonazzi1 Rhonda Brandon1 MicheleCargill1 Ishwar Chandramouliswaran1 Rosane Charlab1 Kabir Chaturvedi1Zuoming Deng1 Valentina Di Francesco1 Patrick Dunn1 Karen Eilbeck1 Carlos Evangelista1 Andrei E Gabrielian1 Weiniu Gan1 Wangmao Ge1Fangcheng Gong1 ZhipingGu1 Ping Guan1 Thomas J Heiman1 Maureen E Higgins1 Rui-Ru Ji1 Zhaoxi Ke1 Karen A Ketchum1 Zhongwu Lai1 YidingLei1Zhenya Li1 Jiayin Li1 Yong Liang1 Xiaoying Lin1 Fu Lu1 Gennady V Merkulov1 Natalia Milshina1 Helen M Moore1 Ashwinikumar K Naik1Vaibhav A Narayan1 Beena Neelam1 Deborah Nusskern1 Douglas B Rusch1 Steven Salzberg12 Wei Shao1 Bixiong Shue1 Jingtao Sun1 Zhen Yuan Wang1Aihui Wang1 Xin Wang1 Jian Wang1 Ming-Hui Wei1 Ron Wides13 Chunlin Xiao1 Chunhua Yan1 Alison Yao1 Jane Ye1 Ming Zhan1 Weiqing Zhang1Hongyu Zhang1 QiZhao1 Liansheng Zheng1 Fei Zhong1 Wenyan Zhong1 Shiaoping C Zhu1 Shaying Zhao12 Dennis Gilbert1 SuzannaBaumhueter1Gene Spier1 Christine Carter1 Anibal Cravchik1 Trevor Woodage1 Feroze Ali1 Huijin An1 Aderonke Awe1 Danita Baldwin1 Holly Baden1 Mary Barnstead1Ian Barrow1 Karen Beeson1 Dana Busam1 Amy Carver1 Angela Center1 Ming LaiCheng1 Liz Curry1 Steve Danaher1 Lionel Davenport1 Raymond Desilets1Susanne Dietz1 Kristina Dodson1 Lisa Doup1 Steven Ferriera1 Neha Garg1 Andres Gluecksmann1 Brit Hart1 Jason Haynes1 Charles Haynes1 CherylHeiner1Suzanne Hladun1 Damon Hostin1 Jarrett Houck1 Timothy Howland1 Chinyere Ibegwam1 Jeffery Johnson1 Francis Kalush1 Lesley Kline1 Shashi Koduru1Amy Love1 Felecia Mann1 David May1 Steven McCawley1 Tina McIntosh1 IvyMcMullen1 Mee Moy1 Linda Moy1 Brian Murphy1 Keith Nelson1Cynthia Pfannkoch1 Eric Pratts1 Vinita Puri1 HinaQureshi1 Matthew Reardon1 Robert Rodriguez1 Yu-Hui Rogers1 Deanna Romblad1 Bob Ruhfel1Richard Scott1 CynthiaSitter1 Michelle Smallwood1 Erin Stewart1 Renee Strong1 Ellen Suh1 Reginald Thomas1 Ni Ni Tint1 Sukyee Tse1 Claire Vech1Gary Wang1 Jeremy Wetter1 Sherita Williams1 Monica Williams1 Sandra Windsor1 Emily Winn-Deen1 KeriellenWolfe1 Jayshree Zaveri1 Karena Zaveri1Josep F Abril14 Roderic Guigoacute14 Michael J Campbell1 Kimmen V Sjolander1 Brian Karlak1 Anish Kejariwal1 Huaiyu Mi1 Betty Lazareva1 Thomas Hatton1Apurva Narechania1 Karen Diemer1 AnushyaMuruganujan1 Nan Guo1 Shinji Sato1 Vineet Bafna1 Sorin Istrail1 Ross Lippert1 Russell Schwartz1Brian Walenz1 ShibuYooseph1 David Allen1 Anand Basu1 James Baxendale1 Louis Blick1 Marcelo Caminha1 John Carnes-Stine1 ParrisCaulk1Yen-Hui Chiang1 My Coyne1 Carl Dahlke1 Anne Deslattes Mays1 Maria Dombroski1 Michael Donnelly1 Dale Ely1 Shiva Esparham1 Carl Fosler1 Harold Gire1Stephen Glanowski1 Kenneth Glasser1 Anna Glodek1 Mark Gorokhov1 Ken Graham1 Barry Gropman1 Michael Harris1 Jeremy Heil1 Scott Henderson1Jeffrey Hoover1 Donald Jennings1 Catherine Jordan1 James Jordan1 John Kasha1 Leonid Kagan1 Cheryl Kraft1 Alexander Levitsky1 Mark Lewis1Xiangjun Liu1 John Lopez1 Daniel Ma1 William Majoros1 Joe McDaniel1 Sean Murphy1 Matthew Newman1 Trung Nguyen1 Ngoc Nguyen1 Marc Nodell1Sue Pan1 Jim Peck1 Marshall Peterson1 William Rowe1 Robert Sanders1 John Scott1 Michael Simpson1 Thomas Smith1 Arlan Sprague1Timothy Stockwell1 Russell Turner1 Eli Venter1 Mei Wang1 Meiyuan Wen1 David Wu1 Mitchell Wu1 Ashley Xia1 Ali Zandieh1 Xiaohong Zhu1
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
bull A 291-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method The 148-billion bp DNA sequence was generated over 9 months from 27271853 high-quality sequence reads (511-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals Two assembly strategies--a whole-genome assembly and a regional chromosome assembly--were used each combining sequence data from Celera and the publicly funded genome effort The public data were shredded into 550-bp segments to create a 29-fold coverage of those genome regions that had been sequenced without including biases inherent in the cloning and assembly procedure used by the publicly funded group This brought the effective coverage in the assemblies toeightfold reducing the number and size of gaps in the final assembly over what would be obtained with 511-fold coverage The two assembly strategies yielded very similar results that largely agree with independent mapping data The assemblies effectively cover the euchromatic regions of the human chromosomes More than 90 of the genome is in scaffold assemblies of 100000 bp or more and 25 of the genome is in scaffolds of 10 million bp or larger Analysis of the genome sequence revealed 26588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ~12000 computationally derived genes with mouse matches or other weak supporting evidence Although gene-dense clusters are obvious almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence Only 11 of the genome is spanned by exons whereas 24 is in introns with 75 of the genome being intergenic DNA Duplications of segmental blocks ranging in size up to chromosomal lengths are abundant throughout the genome and reveal a complex evolutionary history Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function with tissue-specific developmental regulation and with the hemostasis and immune systems DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 21 million single-nucleotide polymorphisms (SNPs) A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average but there was marked heterogeneity in the level of polymorphism across the genome Less than 1 of all SNPs resulted in variation in proteins but the task of determining which SNPs have functional consequences remains an open challenge
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
J C Venter et al Science 291 1304 -1351 (2001)
Fig 2 Flow diagram for sequencing pipeline Samples are received selected and processed in compliance with standard operating procedures with a focus on quality within and across departments Each process has defined inputs and outputs with the capability to exchange samples and data with both internal and external entities according to defined quality guidelines Manufacturing pipeline processes products quality control measures and responsible parties are indicated and are described further in the text
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
httpgenomeucsceducgi-binhgTracksorg=human
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Registro de PubMed
httpwwwncbinlmnihgovSitemapsamplerecordhtml
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
OMICSbull Los estudios ldquoomicsrdquo estaacuten involucrados en el anaacutelisis de cantidades grandes de paraacutemetros
generalmente proteiacutenas (proteomics) liacutepidos (lipidomics) y metabolitos (metabolomics) El teacutermino ldquoomicsrdquo deriva del sufijo griego ldquoomerdquo que significa muchos o masa Las mediciones se hacen a base de marcadores quiacutemicos que son indicativos de alguacuten evento bioloacutegico (biomarkers) Los valores asociados con los paraacutemetros medidos son investigados con el fin de encontrar una correlacioacuten con enfermedades Cuando los objetos de investigacioacuten son proteinas genes y metabolitos las aproximaciones correspondientes son proteomics genomics y metabolommics
bull En antildeos recientes con el desarrollado de meacutetodos para medir y analizar un nuacutemero muy grande de analitos de una sola muestra se ha popularizado las investigaciones que intentan medir miles de paraacutemetros en vez de soacutelo unos cuantos Esta aproximacioacuten es la que dio pie a los experimentos modernos de ldquoomicsrdquo
bull La meta final de las aproximaciones ldquoomicsrdquo es comprender comprehensiva e integralmente los procesos bioloacutegicos mediante la identificacioacuten y correlacioacuten de varios ldquojugadoresrdquo (eg genes RNA proteiacutenas metabolitos) en vez de estudiar cada uno de ellos de manera individual
bull Lamentablemente un estudio sobre la probabilidad de reproducir investigaciones en genomics (asociar grupos de genes con enfermedades complejas) en el cual se compararon 370 estudios reveloacute una alta frecuencia de investigaciones subsecuentes que no confirmaban los descubrimientos iniciales Debido al enorme nuacutemero de mediciones y el nuacutemero limitado de muestras de investigacioacuten surgen problemas relacionados a la estadiacutestica el sesgo la metodologiacutea y el uso inadecuado del meacutetodo
bull
bull Layjr J Liyanage R Borgmann S amp Wilkins C (2006) Problems with the ldquoomicsrdquo TrAC Trendsin Analytical Chemistry 25(11) 1046-1056 doi 101016jtrac200610007
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
OMICrsquoS ARTICULO
Genomics Genomics buzzword or reality
httpviewncbinlmnihgovpubmed10343163
Metabolomics Metabolomic
httpwwwbenthamdirectorgpagescontentphpCDM200800000009000000010011FSGM
Proteomics Proteomics
httpdxdoiorg10109701mnh000007969189474ee
Transcriptomics Transcriptomics
httpviewncbinlmnihgovpubmed18336229
Vaccinomics Vaccinomics
httpwwwgtmborgVOL12BPDF16_Gomase_amp_Tagore_141-146pdf
Oncogenomics Oncogenomics
httpwwwncbinlmnihgovpubmed18336222
Pharmacogenomics Pharmacogenomics
httpwwwncbinlmnihgovpubmed18336223
Epigenomics Epigenomics
httpwwwncbinlmnihgovpubmed18336226
Toxicogenomics Toxicogenomics
httpwwwncbinlmnihgovpubmed18336230
Kinomics Kinomics
httpwwwncbinlmnihgovpubmed18336231
Physiomics Physiomics
httpwwwncbinlmnihgovpubmed18336232
Cytomics Cytomics
httpwwwncbinlmnihgovpubmed18336233
Postgenomics Tracking the shift to postgenomics
httpdxdoiorg101159000092656
Glycomics Probing glycomics
httpdxdoiorg101016jcbpa200611040
Lipidomics Lipidomics is emerging
httpviewncbinlmnihgovpubmed14643793
Cellunomic Cellunomics the interaction analysis of cells
httpviewncbinlmnihgovpubmed19887340
Phylogenomics Phylogenomics evolution and genomics intersection
httpviewncbinlmnihgovpubmed19778869
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
httpbiiiogeekblogspotcom
httplaylamichanunamblogspotcom
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
bull Este proyecto se lleva a cabo gracias al financiamiento de
DGAPA UNAMProyecto PAPIME PE 201509
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
Agradecimientos
bull Laura Montoya
bull Lourdes Valencia
bull Fernando Galicia
bull Roberto Calderoacuten
bull Lyssania Maciacuteas
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
No se nos ha escapado a nuestra atencioacuten que
cuaacutento maacutes exploramos el genoma humano
maacutes nos queda por explorar No cesaremos de
explorar Pues al final de toda exploracioacuten
llegaremos donde empezamos y conoceremos
cuaacutel es nuestro lugar por primera vezldquo
Thomas Stearns Eliot 2001
