BIOINFORMATIKA - fzv.um.si 2 stopnja (učni... · Žitna ulica ñ 2000 Maribor, Slovenija UČNI NAČRTI ŠTUDIJSKO LETO 2019/2020 ŠTUDIJSKI PROGRAM 2. STOPNJE BIOINFORMATIKA

Žitna ulica 15

2000 Maribor, Slovenija

UČNI NAČRTI

ŠTUDIJSKO LETO 2019/2020

ŠTUDIJSKI PROGRAM 2. STOPNJE

BIOINFORMATIKA

1. LETNIK

UČNI NAČRT PREDMETA / COURSE SYLLABUS

Predmet: Algoritmi in podatkovne strukture v bioinformatiki

Course title: Bioinformatics Algorithms and data structures

Študijski program in stopnja Study programme and level

Študijska smer Study field

Letnik Academic year

Semester Semester

Bioinformatika 2. stopnja 1 1

Bioinformatics 2nd degree Bologna Study programme

1 1

Vrsta predmeta / Course type Obvezni predmet / Obligatory subject

Univerzitetna koda predmeta / University course code:

Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial

Lab. vaje Laboratory

work

Teren. vaje Field work

Samost. delo Individ. work

ECTS

30 30 90 6

Nosilec predmeta / Lecturer: Doc. dr. Domen Mongus Doc. dr. Matej Šprogar

Jeziki / Languages:

Predavanja/Lectures: Slovenski/Slovene

Vaje / Tutorial: Slovenski/ Slovene

Pogoji za vključitev v delo oz. za opravljanje študijskih obveznosti:

Prerequisits:

- Osnovna programerska znanja. - Matematična znanja: polinomska,

racionalna, eksponentna in logaritemska funkcija, vektorji in matrike, osnovni pojmi iz teorije grafov.

- Basic programming skills. - Mathematical skills: polynomial, rational,

exponential, logarithmical functions, vectors and matrices, basic knowledge of graph theory.

Vsebina:

Content (Syllabus outline):

- Osnovni pojmi: Kaj je algoritem? Biološki in računalniški algoritmi. Časovna in prostorska zahtevnost. Iterativni in rekurzivni algoritmi.

- Uvod v podatkovne strukture: Objektna orientiranost podatkovnih struktur. Osnovna podatkovna tipa – tabela in povezani seznam. Abstraktni podatkovni tipi - sklad, vrsta in seznam, drevesa, grafi, zgoščena tabela.

- Strategije načrtovanja algoritmov: Naivni pristop. Požrešna metoda. Strategija »deli in vladaj«. Dinamično programiranje. Iskalne strategije. Stohastični algoritmi

- Basic concepts: What is an algorithm? Biological and computer algorithms. Time and space complexity. Iterative and recursive algorithms.

- Introduction to data structures: Object orientation of data structures. Elementary data types – arrays and connected lists. Abstract data types – stack, queue and list, trees, graphs.

- Algorithm design strategies: Brute force. Greedy method. »Divide-and-conquer« strategy. Dynamic programming. Searching strategies. Stochastic algorithms (Monte Carlo algorithms, simulated annealing,

(algoritmi Monte Carlo, simulirano ohlajanje, genetski algoritmi).

- Praktični primeri s področja bioinformatike: Klasifikacija ključnih algoritmov bioinformatike glede na strategijo načrtovanja. Algoritmi nad nizi, zaporedji in drevesi. Analiza zaporedij, iskanje podzaporedij v daljših zaporedjih, poravnava zaporedij, napoved lastnosti proteinov, filogenetska drevesa, fizično mapiranje. Algoritmi nad grafi. Skriti model Markova.

- Algoritmi urejanja: Urejanje s primerjavo ključnih vrednosti. Urejanje v linearnem času.

genetic algorithms). - Practical algorithms of bioinformatics:

Classification with respect to the algorithm design strategy. String algorithms, clustering and trees. Sequence analysis, searching for sub-sequences in longer sequences, sequence alignment, prediction of protein features, phylogenetic trees, physical mapping. Graph algorithms. Hidden Markov models.

- Sorting algorithms: sorting by comparing the key values. Sorting in linear time.

Temeljni literatura in viri / Readings:

- N. C. Jones, P. A. Pevzner: An Introduction to Bioinformatics Algorithms (Computational Molecular Biology), MIT Press, Cambridge, Massachusetts, ZDA, 2004.

- J. Pevzner: Bioinformatics and Functional Genomics, Second Edition, J. Wiley & Sons, Hoboken, New Jersey, ZDA, 2009.

- T. H. Cormen, C. E. Leiserson, R. L. Rivest, C. Stein-: Introduction to Algorithms, Third Edition, MIT Press, Cambridge, Massachusetts, London, Anglija, 2009.

- I. Kononenko, M. Robnik Šikonja: Osnove algoritmov in podatkovnih struktur. Ljubljana, FRI, 2004.

Cilji in kompetence:

Objectives and competences:

Cilji tega predmeta so predstaviti študentom abstraktne podatkovne tipe ter implementacijo le-teh tako s statičnimi tabelami kot z dinamičnimi povezanimi seznami, podati pregled strategij za načrtovanje algoritmov in naučiti študente primerno izbirati te strategije v konkretnih praktičnih problemih, naučiti študente vloge analize zahtevnosti pri načrtovanju algoritmov ter implementirati nekaj tipičnih problemov s področja bioinformatike.

The objectives of this course are to represent to the students basic data structures and their implementation using static and dynamic data types, to introduce the basic algorithm strategies and to teach the students how to select among them in concrete problems, to teach the students to analyze the algorithms regarding time and space complexity, and to implement some selected problems from bioinformatics.

Predvideni študijski rezultati:

Intended learning outcomes:

Znanje in razumevanje: Študentje:

- se bodo zavedali pomena podatkovnih struktur in ustrezne izbire le-teh pri načrtovanju algoritmov,

- spoznali bodo osnovni podatkovni strukturi (tabelo in povezani seznam),

- spoznali bodo abstraktne podatkovne tipe (sklad, vrsta, seznam, zgoščena tabela, drevesa, iskalna drevesa, grafi) in operacije nad njimi ter jih implementirali s pomočjo ustreznih pretvorb v osnovne podatkovne tipe,

Knowledge and understanding: The students will:

- be aware of selecting the suitable data structures and their use at algorithms design,

- understand the fundamental data structures and master their implementations,

- know the fundamental strategies for algorithms design,

- be able to determine the time and space complexity of the algorithms,

- poznali bodo strategije načrtovanja algoritmov,

- znali bodo analizirati prostorsko in časovno zahtevnost algoritmov,

- razumeli bodo ozadje računalniške predstavitve in reševanja mnogih problemov s področja bioinformatike.

- Študentje bodo največkrat znali primerno uskladiti podatkovne strukture in strategije načrtovanja algoritmov.

- Implementirane podatkovne strukture bodo rutinirano uporabljali tako med študijem kot pri kasnejšem delu.

- Pri načrtovanju algoritmov bodo smotrno iskali kompromise med kriteriji, kot so časovna zahtevnost, prostorska zahtevnost, kakovost in točnost rešitve...

- Izkušnje, pridobljene z implementacijo in študijem delovanja v mnogih splošnih primerih, bodo znali uporabiti v konkretnih praktičnih aplikacijah s področja bioinformatike.

- get the computing background for different problems of bioinformatics.

- The students will be able to harmonize the usage of data structures and algorithm strategies at practical problems.

- The students will skilfully use implemented data structures and algorithms during the study and later work.

- At algorithm design they will reasonable search the compromises among different criteria as difficultness of implementation, time and space complexity and quality of the solution.

- They will be able to use the knowledge and practical experience at different problems of bioinformatics.

Metode poučevanja in učenja:

Learning and teaching methods:

Predavanja, razgovor, demonstracija, računalniške vaje.

Lectures, discussions, demonstration, computer exercises.

Načini ocenjevanja:

Delež (v %) / Weight (in %)

Assessment:

Naloge (računalniške vaje),

pisni izpit.

50 % 50 %

coursework (practical assignments),

written examination.

Reference nosilca / Lecturer's references:

DOMEN MONGUS HORVAT, Denis, ŽALIK, Borut, RUPNIK, Marjan, MONGUS, Domen. Visualising the attributes of biological cells, based on human perception. V: HOLZINGER, Andreas (ur.), PASI, Gabriella (ur.). Lecture notes in computer science, ISSN 0302-9743, Lecture notes in artificial intelligence, vol. 7947. Berlin; Heidelberg: Springer, 2013, str. 386-399. DOMEN MONGUS ŠKRABAN, Jure, DŽEROSKI, Sašo, ŽENKO, Bernard, MONGUS, Domen, GANGL, Simon, RUPNIK, Maja. Gut microbiota patterns associated with colonization of different clostridium difficile ribotypes. PloS one, ISSN 1932-6203, 2013, vol. 8, iss. 2, str. e58005-1-e58005-13, doi: 10.1371/journal.pone.0058005 DOMEN MONGUS ŽALIK, Borut, MONGUS, Domen, LUKAČ, Niko. A universal chain code compression method. Journal of visual communication and image representation, ISSN 1047-3203, May 2015, vol. 29, str. 8-15, doi: 10.1016/j.jvcir.2015.01.013.

ŠPROGAR, Matej, PODGORELEC, Vili Incremental approach to structurally difficult problems in genetic programming. Elektronika ir elektrotechnika, ISSN 1392-1215. [Print ed.], 2014, vol. 20, no. 5, str. 154-157. PODGORELEC, Vili, ŠPROGAR, Matej, POHOREC, Sandi. Evolutionary design of decision trees. Wiley interdisciplinary reviews, Data mining and knowledge discovery. [Print ed.], 2013, vol. 3, iss. 2, str. 63-82.


Predmet: Informacijsko komunikacijske tehnologije v bionformatiki

Course title: Informarion and communication technologies for bioinformatics




Semester Semester

Bioinformatika 2. stopnja Bioinformatika 1 1


Bioinformatics 1 1



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial


work



ECTS

18 42 90 6

Nosilec predmeta / Lecturer: Red. prof. dr. Milan Zorman Doc. dr. Domen Verber

Jeziki / Languages:

Predavanja/Lectures: slovenski/slovene

Vaje / Tutorial: slovenski/slovene


Prerequisits:

V predmet se lahko vključijo vsi redno vpisani študenti v magistrski študijski program Bionformatika s predizobrazbo naravoslovne ali zdravstvene smeri

This subject can be selected by all regularly registered students of Master's degree study programme Bioinformatics with the background in health or natural sciences

Vsebina:


1. Zgodovina računalništva, 2. Von Neumanov model arhitekture, osebni

računalnik 3. Sestavni deli računalnika: aritmetična in

krmilna enota, pomnilnik, vhodno izhodne enote

4. Programska in materialna oprema 5. Podatkovne zbirke: vrste in namen,

podatkovno modeliranje, relacijske zbirke, bibliografske zbirke

6. Omrežja in splet 7. Računalništvo in biologija 8. Računalniška orodja v bionformatiki 9. Vizualzacija 10. Programiranje za bioinformatiko v jeziku

1. History of computing 2. Von Neumans Arhitecture, personal

computer 3. Input/output units, central processing unit 4. Software and hardware 5. Data bases, 6. Networks and world wide web 7. Computers in biology 8. Computer tools in bioinformatics 9. Visualisation 10. Programming for bioinformatics in Java

Java

Temeljna literatura in viri / Readings:

E. Turban, R. K. Rainer Jr., R. E. Potter: Introduction to Information Technology. 3rd ed., Wiley, 2004.

P. Kokol: Računalništvo v zdravstvu I. Maribor: NICE textbooks from the Phare Tempus program. Visoka zdravstvena šola, 1998.

C. Gibas, P. Jambeck. Developing Bioinformatics Computer Skills: OReily and Associates, 2001

U.Mesojedec, B.Fabjan: Java 2:temelji programiranja, Pasadena, 2004.

spletni viri / internet sources



Študent bo pridobil napredna znanja o računalniku in računalniških orodjih in metodah, ki se uporabljajo v bioinformatiki.

Student will learn the advanced contents of computer science and methods, used in the field of bioinformatics.



Znanje in razumevanje: Diplomant:

Spozna enote računalnika in njihovo delovanje

Spozna umeščenost računalnika v zdravstvenih sistemih povezanih z bioinformatiko

Spozna osnove programske in strojne opreme

Se nauči osnovnih veščin upravljanja podatkovnih baz

Spozna pomen informacijske tehnologije v biologiji

Spozna osnove vizualizacije podatkov

Spozna osnove programiranja v jeziku Java

Knowledge and understanding: Student:

Learns the computer architecture and its working principles

Understands the role of the computer in the health systems related to informatics

Learns about software and hardware

Learns the basics of management of databases

Understands the role of information technology in biology

Learns the basics of visualisation

Learns the basics of Java programming



Predavanja, seminarji. Lectures, seminar work.



Assessment:

Način (pisni izpit, ustno izpraševanje, naloge, projekt) Pisni izpit, projekt.

50 50

Type (examination, oral, coursework, project): Written exam, project.


ZORMAN, Milan Classification of follicular lymphoma images : a holistic approach with symbol-based machine learning methods / Milan Zorman, José Luis Sánches de la Rosa, Dejan Dinevski. - Graf. prikazi. - Abstract ;

Zusammenfassung. - Bibliografija: str. 708-709. V: Wiener Klinische Wochenschrift. - ISSN 0043-5325.. - Jg. 123, Heft 23/24 (2011), str. 700-709. COBISS.SI-ID 15706134, JCR ZORMAN, Milan Opening the knowledge tombs - web based text mining as approach for re-evaluation of machine learning rules / Milan Zorman, Sandi Pohorec and Boštjan Brumen. - Abstract. - Bibliografija: str. 542. V: Lecture notes in computer science. - ISSN 0302-9743. - Vol. 6295 (2010), str. 533-542. COBISS.SI-ID 14444310 ZORMAN, Milan Explanatory approach for evaluation of machine learning-induced knowledge / M. Zorman and M. Verlič. - Abstract. - Bibliografija: str. 1550-1551.V: Journal of international medical research. - ISSN 0300-0605.. - Letn. 37, št. 5 (2009), str. 1543-1551. COBISS.SI-ID 13645334, JCR VERBER, Domen Implementation of non-intrusive fault detection in embedded control systems / Domen Verber, Matej Šprogar, Matjaž Colnarič. - Bibliografija: str. 30. V: Informacije MIDEM. - ISSN 0352-9045.. - Letn. 37, št. 1(121) (mar. 2007), str. 23-30. COBISS.SI-ID 11552534, JCR VERBER, Domen Utilization of high performance computing in everyday business applications / Domen Verber. - Ilustr. - Bibliografija: str. [5]. - Abstract. V: The proceedings of the 2nd International Conference on Information Society and Information Technologies - ISIT 2010, [Dolenjske Toplice, 10-12 November 2010] / edited by Matej Mertik. - Novo mesto : Faculty of Information Studies, 2010. - ISBN 978-961-92509-5-2. - [5] str. COBISS.SI-ID 14700054 VERBER, Domen Decentralized fault and resource management for distributed control systems / Domen Verber. V: Applications of systems science / editors Adam Grzech, Paweł Świątek, Krysztof Brzostowski. - Warsaw : EXIT, cop. 2010. - ISBN 978-83-60434-78-9. - Str. 237-243. COBISS.SI-ID 14487574


Predmet: Izbrana poglavja iz biofizike

Course title: Selected topics in Biophysics




Semester Semester



Bioinformatics 1 1

Vrsta predmeta / Course type Izbirni predmet / Optional subject


Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial


work



ECTS

30 30 90 6

Nosilec predmeta / Lecturer: Doc. dr. Aleš Fajmut

Jeziki / Languages:




Prerequisits:

Posebnih pogojev ni. Za študente, ki na 1. stopnji univerzitetnega študijskega programa niso osvojili osnovnih znanj fizike, morajo izbrati ta predmet.

No special prerequisites required. However, for all students that have not gained the knowledge of fundamental physics in the 1. level of university degree this subject is compulsory.

Vsebina:


Mehanika: sila, tlak, navor, delo, energija, moč; deformacije; hidrostatika in hidrodinamika. Električni in magnetni pojavi; električno in magnetno polje. Termodinamika: termodinamični zakoni, termodinamični potenciali, toplotni in snovni tokovi. Nihanje in valovanje: zvok, svetloba; osnovne lastnosti valovanja, geometrijska optika. Ključni eksperimenti moderne fizike. Zgradba in model atoma, medatomske in medmolekulske interakcije. Zgradba in stabilnost atomskega jedra, radioaktivnost. Izbranih zgledi iz biologije:

1. Biomehanika: sile v kosteh in mišicah; delovanje krvožilnega sistema in transport respiratornih plinov; mehanske lastnosti biološke membrane, oblika in spremembe oblik celice.

2. Termodinamika: 1. zakon termodinamike in metabolizem, toplota, delo in moč organizma; 2. zakon termodinamike in pogoji minimalne proste energije ter maksimalne entropije v bioloških sistemih; regulacijski sistemi in mehanizmi, regulacija telesne temperature, regulacija volumna celice.

3. Elektromagnetizem: difuzija ionov Donnanovo ravnovesje, membranski potencial; akcijski potencial in širjenje električnega pulza po živčni celici, magnetno polje in orientacija organizmov, šibka magnetna polja

4. Nihanje in valovanje: celični in biokemijski oscilatorji; zvok in uho, svetloba in oko.

5. Molekularna biofizika: medatomske in medmolekularne interakcije in kemijske vezi. Vpliv ionizirajočega sevanja na organizem.

Študent opravi 10 laboratorijskih vaj iz področij mehanike, termodinamike, električnih in magnetnih pojavov, valovne in geometrijske optike, moderne fizike in radioaktivnosti. Vsebina vaj je aplicirana na biološke sisteme.

Mechanics: force, pressure, torque, work, energy, power; deformations; hydrostatics and hydrodynamics. Electricity and magnetism; electric and magnetic fields. Thermodynamics: thermodynamic laws and potentials, heat and mass flow. Oscillations and waves: sound, light; properties of waves, geometric optics. Experiments essential in modern physics. Structure and models of atoms, atomic and intermolecular interactions. Structure and stability of atomic nucleus, radioactivity. Selected illustrative examples from biology:

1. Biomechanics: forces in bones and muscles; flow of blood in the circulatory system; transport of respiratory gases; mechanical properties of biological membranes, cell shape and its transformation.

2. Thermodynamics: the first law of thermodynamics, metabolism, heat, work and power of human and animals; the second law of thermodynamics, conditions of minimal free energy and maximal entropy in biological systems; regulatory systems and mechanisms, body temperature regulation, cell volume regulation.

3. Electromagnetism: diffusion of ions, the Donnan equilibrium, membrane potential; action potential and nerve impulses; magnetic fields and orientation of organisms, weak magnetic fields in biology

4. Vibrational and wave motion: biochemical and cellular oscillators; sound and an ear, ultrasound; light, an eye.

5. Molecular biophysics: atomic and molecular interactions and chemical bonds. Biological effects of ionizing radiation.

Students perform 10 laboratory experiments from mechanics, thermodynamics, electricity and magnetism, wave nature of light and geometric optics, atomic physics and radioactivity. The content of labor work is applied to biological systems.


R. Kladnik: Visokošolska fizika, 1. del: Mehanika in toplotni pojavi, 2. del: Elektrika, Atomika, 3. del: Valovni pojavi, Akustika in optika, Državna založba Slovenije, Ljubljana 1989 R. Glaser: Biophysics, Springer, Berlin 2001 G. B: Benedek, F. M. H. Villars: Physics with Illustrative Examples from Medicine and Biology: Mechanics, Statistical Physics, Electricity and Magnetism, Springer, New York 2000 P. R. Bergethon: The Physical Basis of Biochemistry. The Foundations of Molecular Biophysics, Springer, New York 1998 Interna navodila za izvedbo eksperimentalnih vaj/ Guidelines for labor work.



Osvojiti fizikalne koncepte in zakonitosti pomembne za razumevanje bioloških procesov.

The main objective is to gain the knowledge of physical concepts and laws which are essential for understanding the biological processes.



Znanje in razumevanje: Študent osvoji znanje o strukturi bioloških sistemov in njihovo delovanje razume na osnovi fizikalnih konceptov in zakonitosti. Prenesljive/ključne spretnosti in drugi atributi: Študent zna uporabiti preproste matematične modele za kvantitativno obravnavo strukture in funkcije bioloških sistemov.

Knowledge and Understanding: Students get knowledge of structure and function of selected biological systems based on the fundamental principles and concepts of physics. Transferable/Key Skills and other attributes: Students are able to use simple mathematical models for quantitative studies of structure and function of biological systems.



Predavanja Laboratorijske vaje z ustreznimi računskimi vajami

Lectures Labor work with concomitant mathematical exercises in problem solving



Assessment:

Način (pisni izpit, ustno izpraševanje, naloge, projekt) Pisni kolokvij ob zaključku laboratorijskih vaj Pisni izpit Ustni izpit

30%

30% 40%

Type (examination, oral, coursework, project): Written test on labor work Written exam. Oral exam.


FAJMUT, Aleš MLC-kinase/phosphatase control of Ca[sup]2+ signal transduction in airway smooth muscles / Aleš Fajmut, Milan Brumen. - . - Dostopno tudi na: http://dx.doi.org/10.1016/j.jtbi.2007.10.005. - Available online Oct. 11 2007. - Bibliografija: str. 481. V: Journal of theoretical biology. - ISSN 0022-5193.. - Vol. 252, no. 3 (2008), str. 474-481. . - doi: 10.1016/j.jtbi.2007.10.005 COBISS.SI-ID 15856392, JCR, WoS, št. citatov do 6. 5. 2011: 5, brez

avtocitatov: 4, normirano št. citatov: 2 CONTRIBUTION of Rho kinase to the early phase of the calcium-contraction coupling in airway smooth muscle / Prisca Mbikou ... [et al.]. - Ilustr. - Nasl. z nasl. zaslona. - Opis vira z dne 7. 12. 2010. - Soavtorji: Ales Fajmut, Milan Brumen, Etienne Roux. - Bibliografija: str. 257-258. - Abstract. V: Experimental physiology. - ISSN 0958-0670.. - Vol. 96, issue 2 (2011), str. 240-258. . - doi: 10.1113/expphysiol.2010.054635 COBISS.SI-ID 18009864, JCR, WoS, št. citatov do 10. 4. 2012: 2, brez avtocitatov: 2, normirano št. citatov: 1 DOBOVIŠEK, Andrej Role of expression of prostaglandin synthases 1 and 2 and leukotriene C [sub] 4 synthase in aspirin-intolerant asthma: a theoretical study / A. Dobovišek, A. Fajmut, M. Brumen. - Bibliografija: str. 277-278. - Abstract.V: Journal of pharmacokinetics and pharmacodynamics. - ISSN 1567-567X.. - Vol. 38, no. 2 (2011), str. 261-278. . - doi: 10.1007/s10928-011-9192-6 COBISS.SI-ID 18203144, JCR, WoS, št. citatov do 6. 4. 2012: 1, brez avtocitatov: 0, normirano št. citatov: 0


Predmet: Izbrana poglavja iz mikrobiologije in biokemije

Course title: SELECTED TOPICS IN MICROBIOLOGY AND BIOCHEMISTRY




Semester Semester



Bioinformatics 1 1



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial


work



ECTS

30 30 90 6

Nosilec predmeta / Lecturer: Izr. prof. dr. Sabina Fijan

Jeziki / Languages:




Prerequisits:

Poznavanje osnov mikrobiologije, molekularne biologije in biokemije

Understanding basics of microbiology, molecular biology and biochemistry

Vsebina:


Osnovne značilnosti mikroorganizmov: glavne skupine mikroorganizmov, hranilne potrebe, rast in življenjski pogoji mikroorganizmov, zgodovina mikrobiologije in molekularne biologije, probiotiki. Značilnosti bakterij, gliv, virusov; glavni predstavniki mikroorganizmov. Vloga mikroorganizmov v C, N, S in P ciklih. Osnove kemične zgradbe (od atomov do molekul do celic). Ogljikovi hidrati: zgradba in biološka vloga. Lipidi: zgradba in biološka vloga, biološke membrane, transport. Proteini: aminokisline, peptidi, tridimenzionalna zgradba, biološka vloga. Encimi: reakcije, kinetika, inhibicija, koencimi, . Nukleinske kisline: DNK, RNK, zgradba in biokemijske lastnosti. Vitamini; Hormoni. Temelji celičnega metabolizma. Metabolizem ogljikovih hidratov. Glikoliza, citratni cikel, veriga za prenos elektronov in nastanek ATP). Metabolizem maščobnih kislin in lipidov. Metabolizem aminokislin in drugih dušikovih spojin.

Basic characteristics of microorganisms: main groups of microorganisms, growth and environmental conditions of microorganisms, history of microbiology and molecular biology, probiotics. Characteristics of bacteria, fungi, viruses; main representatives of microorganisms. The role of microorganisms in global C, N, S and P cycles. Basic biochemical structures From atoms to molecules to cells, Carbohydrates: Structure and Biological Function. Lipids: Structure and Biological Function, Biological Membranes and Cellular Transport. Proteins: amino acids, peptides, and proteins, protein architecture and biological function Enzymes: reactions, kinetics, inhibition, coenzymes. Nucleic acids; DNA and RNA: Structure and function. Vitamins; Hormones. Basic Concepts of Cellular Metabolism. Metabolism of Carbohydrates. Glycolysis, the citric acid cycle, electron-transport chain and ATP formation. Metabolism of fatty acids and other lipids. Metabolism of amino acids and other nitrogenous compounds.


FIJAN, S. (2014). Izbrana poglavja iz mikrobiologije in biokemije : navodila za vaje s teoretičnimi osnovami za študente podiplomskega študija bioinformatike, 2. stopnja na FZV UM : (za interno uporabo). Maribor: Fakulteta za zdravstvene vede.

Dragaš, A.Z. (1998). Mikrobiologija z epidemiologijo. Ljubljana: DZS.

Godič Torkar, K Zore, A. (2010). Mikrobiologija s parazitologijo: učbenik za vaje. Ljubljana: Zdravstvena fakulteta.

Burton G.R.W., Engelkirk P.G. (2000). Microbiology for the health sciences. Philadelphia: Lippincott Williams & Wilkins.

Boyer, Rodney F. (2005). Temelji biokemije [prevajalci Abram V, et al.]. Ljubljana: Študentska založba.

L. STRAYER et al.: Biochemistry, 4th ed, W.H. Freeman and Company, New York, 1995

http://cobiss6.izum.si/scripts/cobiss?ukaz=DISP&id=1232138697183008&rec=30&sid=1

http://cobiss6.izum.si/scripts/cobiss?ukaz=SEAL&mode=5&id=1232138697183008&PF=AU&term=%22Godi%C4%8D%20Torkar,%20Karmen%22

http://cobiss6.izum.si/scripts/cobiss?ukaz=SEAL&mode=5&id=1232138697183008&PF=AU&term=%22Godi%C4%8D%20Torkar,%20Karmen%22

http://cobiss6.izum.si/scripts/cobiss?ukaz=SEAL&mode=5&id=1232138697183008&PF=AU&term=%22Boyer,%20Rodney%20F.%22



Študenti bodo seznanjeni z osnovnimi značilnostmi mikroorganizmov, njihovimi rastnimi pogoji ter s strukturnimi značilnostmi in lastnostmi glavnih skupin biomolekul ter njihovo vlogo v metabolizmu in ostalih bioloških procesih.

Students will be provided with knowledge on the basic characteristics of microorganisms and their growth conditions as well as structural characteristics of major groups of biomolecules and their role in cell metabolism and other important biological processes.



Znanje in razumevanje:

Osnovne značilnosti mikroorganizmov

strukturne značilnosti biomolekul

vloga biomolekul v celičnih procesih

Knowledge and Understanding:

basic characteristics of microorganisms

structural characteristics of biomolecules

the role of biomolecules in cell function



Predavanja

Laboratorijske vaje

Lectures

Tutorial



Assessment:

Način (pisni izpit, ustno izpraševanje, naloge, projekt)

pisni in

ustni izpit 70 30

Type (examination, oral, coursework, project):

writen and

oral exemination


1. FIJAN, Sabina. Microorganisms with claimed probiotic properties: an overview of recent literature. International journal of environmental research and public health, ISSN 1660-4601, 2014, vol. 11, no. 5, str. 4745-4767.

2. FIJAN, Sabina, ŠOSTAR-TURK, Sonja. Inactivation of Enterococcus faecium in water and hospital laundry wastewater by disinfection processes utilizing peroxyacetic acid or ultraviolet radiation. Journal of pure & applied microbiology, ISSN 0973-7510, 2014, vol. 8, no. 1, str. 531-538,

3. FIJAN, Sabina, ROZMAN, Urška, ŠOSTAR-TURK, Sonja. Comparing the detection of various microorganisms on metal and glass surfaces using incubation methods on selective agars, modified PCR methods and simultaneous detection by a unified parallel PCR method. Journal of pure & applied microbiology, ISSN 0973-7510, 2013, vol. 7, no. 3, str. 1535-1546.

4. FIJAN, Sabina, STEYER, Andrej, POLJŠAK-PRIJATELJ, Mateja, CENCIČ, Avrelija, ŠOSTAR-TURK, Sonja, KOREN, Srečko. Rotaviral RNA found on various surfaces in a hospital laundry. J. virol. methods. [Print ed.], Mar. 2008, vol. 148, iss. 1/2, str. 66-73.

5. FIJAN, Sabina, KOREN, Srečko, CENCIČ, Avrelija, ŠOSTAR-TURK, Sonja. Antimicrobial disinfection effect of a laundering procedure for hospital textiles against various indicator bacteria and fungi using different substrates for simulating human excrements. Diagn. microbiol. infect. dis.. [Print ed.], Mar. 2007, vol. 57, iss. 3, str. 251-257.


Predmet: Kemija

Course title: Chemistry




Semester Semester



Bioinformatics 1 1



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial


work



ECTS

30 30 90 6

Nosilec predmeta / Lecturer: Red. prof. dr. Željko Knez

Jeziki / Languages:




Prerequisits:

Ni pogojev. None.

Vsebina:


Kemijske vezi, medmolekulske sile,

Voda: struktura, lastnosti, H vez, voda kot topilo,

pH, ionizacija vode, Kw, pH, šibki in mocni elektroliti, kisline in baze (titracijske krivulje, Ka, Kb, pKa, pKb), pufri, puferski sistemi v organizmu, biološki pomen pH,

Raztopine: raztapljanje plinov v vodi (Henryjev zakon), koligativne lastnosti raztopin (Raultov zakon, znižanje zmrzišča, zvišanje vrelišca, osmozni tlak), osmozni pojavi v celici (tonicnost, Donnanovo ravnotežje, pasivni transport – Fickov zakon),

Oksidacija - redukcija: definicije, kvantitativna karakterizacija redoks reakcij,

Redoks potencial in reakcijska prosta entalpija,

Chemical bonds, forces between molecules

Water: structure, characteristics, H bond, water as dissolvent

pH, water ionization, Kw, pH, weak and strong electrolyte, acids and bases (titration curves, Ka, Kb, pKa, pKb), pufer, pufer systems in organism, biological meaning of pH

Solutions: gas dissolving in water (Henry law) koligativno characteristics of solutions (Rault law, decreasing of freezing point, increasing of boiling point, osmotic pressure), osmotic phenomenon in cell (Donnans balance, passive transport – Fickos law)

Oxidation – reduction : definitions, quantitative characterization redox reactions

Hitrost kemijskih reakcij: definicije, red reakcije,

Osnove prenosnih pojavov,

Molekulske osnove življenja: biološko pomembni elementi, ioni in molekule,

Organske molekule: izomerija, medsebojni vpliv funkcionalnih skupin (induktivni in resonancni efekt),

Kratek pregled organskih spojin po funkcionalnih skupinah.

Kratek pregled kemije: - ogljikovih hidratov

(monosaharidi, disaharidi, polisaharidi),

- lipidov in steroidov (steroidi, steroli, žolčne kisline, steroidni hormoni – struktura),

- aminokislin, - nukleotidov in nukleinskih

kislin.

Redox potential and free reaction enthalpy,

Velocity of chemical reactions: definitions,

Basics of transportability phenomenon,

Molecular basics of life: biological important elements, ions and molecules,

Organics molecules: isomerism, mutual influence of functional groups (inductive and resonant effect),

Short overview of organic compound by functional groups.

Short review of chemistry: - carbon hydrates (monosaccharide,

disaccharide, polysaccharide) - lipid and steroids (steroids, steroli, gall acid,

steroids hormones,- structure) - aminoacid, - nucleotides and nucleic acid.


- Lazarini F., Brencic J.: Splošna in anorganska kemija, 3. izd. Ljubljana : Državna založba Slovenije, 1992

- Lehninger A.L., Nelson D.L., Cox M.M., Waites J.: Principles of biochemistry : with an extended discussion of oxygen-binding proteins, 2nd ed., 9th printing, New York : Worth, 2000.

- Hunt, Harold R., Block, Toby F., McKelvy, George M.: Laboratory experiments for general chemistry, 4th ed., Australia, United States : Brooks/Cole-Thomson Learning, 2002. Strauss S.H.: Guide to solutions for Inorganic chemistry: 3rd ed. Oxford University Press, 1999.

- William Walter Ogilvie, Nathan Ackroyd, C. Scott Browning, Ghislain Deslongchamps, Felix Lee, Effie Sauer, Organic Chemistry: A Mechanistic View, Nelson Education Limited, 2017.

- Joseph C. Muhler, Inorganic Structural Chemistry, 2nd Edition, John Wiley & Sons Inc, 2006.



Študent si pridobi znanje iz splošne kemije, spozna kemijsko zgradbo organskih molekul in reakcije, ki med njimi potekajo z namenom bolje razumeti kemijske reakcije, ki potekajo v organizmu

Student will gain knowledge of general chemistry, get familiar with chemical structure of organic molecules and reactions between them to better understand the reactions in organism.



Znanje in razumevanje: Študent bo razumel izbrane kemijske pojme.

Knowledge and understanding: Student will be able to understand selected chemical concepts.



Predavanja, seminarji, delavnice. Lectures, seminar work, workshops.

Delež (v %) /

Načini ocenjevanja: Weight (in %) Assessment:

Način (pisni izpit, ustno izpraševanje, naloge, projekt) opravljen seminar ustni pisni izpit

40 30 30

Type (examination, oral, coursework, project): Seminar Oral exam Written exam


KNEZ, Željko, ŠKERGET, Mojca, KNEZ HRNČIČ, Maša. Principles of supercritical fluid extraction and applications in the food, beverage and nutraceutical industries. V: RIZVI, Syed S. H. (ur.). Separation, extraction and concentration processes in the food, beverage and nutraceutical industries. Oxford [etc.]: Woodhead Publishing Limited, 2010. KNEZ, Željko, KNEZ HRNČIČ, Maša, ČOLNIK, Maja, ŠKERGET, Mojca. Chemicals and value added compounds from biomass using sub- and supercritical water. The Journal of supercritical fluids, ISSN 0896-8446. [Print ed.], Available online 30 August 2017. ŠPANINGER, Eva, KNEZ HRNČIČ, Maša, ŠKERGET, Mojca, KNEZ, Željko, BREN, Urban. Polyphenols : extraction methods, antioxidative action, bioavailability and anticarcinogenic effects. Molecules, ISSN 1420-3049, 2016, vol. 21, no. 7, str. 1-38.


Predmet: MOLEKULARNA BIOFIZIKA

Course title: MOLECULAR BIOPHYSICS




Semester Semester

Bioinformatika 2. stopnja Bioinformatika 1 1 2


Bioinformatics 1 1 2



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial


work



ECTS

30 30 90 6

Nosilec predmeta / Lecturer: doc. dr. Aleš Fajmut

Jeziki / Languages:




Prerequisits:

Znanje fizike v obsegu splošnega univerzitetnega kurza fizike ali biofizike za nefizikalne študijske smeri.

Knowledge of physics on the level of a general university course in physics or biophysics given to students of studies others than physics.

Vsebina:


1. Struktura in funkcija bioloških makromolekul in ostalih gradnikov živih bitij. Kemijske vezi, medatomske in medmolekularne interakcije. Struktura proteinov in načini modeliranja njihove tridimenzionalne strukture. 2. Biofizika celične membrane in celice. Električni membranski potencial. Transport preko celične membrane. Mehanizmi znotrajcelične in medcelične signalizacije in komunikacija. 3. Termodinamski opis biokemijskih reakcij 4. Pregled nekaterih eksperimentalnih metod v molekularni biofiziki.

1. Structure and function of biological macromolecules and other building blocks of livving matter. Chemical bonds, intra- and intermolecular forces. Structure of proteins and its modelling. 2. Biophysics of cell membrane and cell Transport across the cell membrane. Mechanisms of intra and intercellular signalisation and communications. 3. Thermodynamic description of biochemical reactions 4. Outline of selected experimental methods in molecular biophysics.


J.A. Tuszynski, M. Kurzynski: Introduction to Molecular Biophysics, CRC Press 20

R. Glaser: Biophysics, Springer, New York 2004

P. R. Bergethon: The Physical Basis of Biochemistry. The Foundations of Molecular Biophysics, Springer, New York 1998

I. N. Serdyuk, N. R. Zaccai, J. Zaccai: Methods in Molecular Biophysics (Structure, Dynamics, Function), Cambridge Press, 2007



Študent osvoji znanje o strukturi in funkciji bioloških sistemov oziroma njihovih gradnikov na različnih ravneh organiziranosti in kompleksnosti bioloških sistemov in sicer na molekularni in makromolekularni ravni, na stopnji supramolekularne organiziranosti, na ravni celice in tkiva. Celoten kurz temelji na konceptih in metodah teoretične biofizike. Znanje o bioloških sistemih na molekularni ravni, ki je nujno potrebno za delo s podatki in podatkovnimi bazami v bioinformatiki.

Students get knowledge of structure and function of biological systems with respect to different levels of organisation and complexity, from molecules, macromolecules and supramolecular structures to the cell and tissue. The approach is based on concepts and methods of theoretical biophysics. Knowledge of biological systems on molecular level that is essential to deal with the data and data bases in bioinformatics.



Znanje in razumevanje: Študent osvoji znanje o strukturi bioloških sistemov in njihovo delovanje razume na osnovi fizikalnih konceptov in zakonitosti.

Knowledge and understanding: Students get knowledge and understanding of structure and function of selected biological systems based on principles and concepts of physics.



Predavanja Seminarska naloga iz izbranega področja iz biofizike. Seminarske oziroma računske vaje.

Lectures Coursework from selected field in biophysics Tutorials



Assessment:

Način (pisni izpit, ustno izpraševanje, naloge, projekt) Pisni izpit Ustni izpit Seminarska naloga

35% 35% 30%

Type (examination, oral, coursework, project): Written exam Oral exam Course work


1. DOBOVIŠEK, Andrej, VITAS, Marko, BRUMEN, Milan, FAJMUT, Aleš. Energy conservation and maximal entropy production in enzyme reactions. Biosystems, ISSN 0303-2647. [Print ed.], 2017, vol. 158, str. 47-56, doi: 10.1016/j.biosystems.2017.06.001. [COBISS.SI-ID 23218696] 2. FAJMUT, Aleš, EMERŠIČ, Tadej, DOBOVIŠEK, Andrej, ANTIĆ, Nataša, SCHÄFER, Dirk, BRUMEN, Milan. Dynamic model of eicosanoid production with special reference to non-steroidal anti-inflammatory drug-triggered hypersensitivity. IET systems biology, ISSN 1751-8849. [Print ed.], 2015, vol. 9, iss. 5, str. 204-215,

doi: 10.1049/iet-syb.2014.0037. [COBISS.SI-ID 21404168] 3. GOSAK, Marko, MARKOVIČ, Rene, FAJMUT, Aleš, MARHL, Marko, HAWLINA, Marko, ANDJELIĆ, Sofija. The analysis of intracellular and intercellular calcium signaling in human anterior lens capsule epithelial cells with regard to different types and stages of the cataract. PloS one, ISSN 1932-6203, 2015, vol. 10, iss. 12. http://dx.doi.org/10.1371/journal.pone.0143781, doi: 10.1371/journal.pone.0143781. [COBISS.SI-ID 2645676]


Predmet: Multivariatne statistične metode

Course title: Multivariate statistical methods




Semester Semester

Bioinformatika 2. stopnja Bioinformatika 1 2 1


Bioinformatics 1 2 1



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial


work



ECTS

30 30 90 6

Nosilec predmeta / Lecturer: Doc. dr. Petra Povalej Bržan

Jeziki / Languages:




Prerequisits:

Poznavanje osnov statistike,

osnove podatkovnih baz,

osnovno poznavanje programskega paketa SPSS.

Basics of statistics,

basics of databases,

basics of software package SPSS.

Vsebina:


Osnovni pojmi : • Podatek • Spremenljivka • Hipoteza • Porazdelitev • Podatkovni tipi

Osnove statistične analize podatkov: • Priprava podatkov za statistično analizo • Deskriptivna analiza podatkov • Normalna porazdelitev • Ostale porazdelitve • Postavitev hipotez • Korelacija • Univariatna analiza

Grafična predstavitev podatkov za multivariatno analizo:

Basics: • Data • Identifiers • Hypothesis • Distribution • Data types

Introduction to statistical data analysis: • Data preprocessing • Descriptive data analysis • Normal distribution • Other distributions • Generating hypotheses • Correlations • Univariate analysis

Graphical representation of data for multivariate

• Razsevni grafikon • Večkratni matrični grafikon • Polarni grafikon • Multidimenzionalno skaliranje

Uvod v multivariatno analizo: • Priprava podatkov • Večrazsežna normalna porazdelitev • Normalizacija • Postavitev hipotez

Pregled metod multivariatne analize: • MANOVA • Analiza kovariance • Klastrska analiza • Linerana regresija • Logistična regresija

Praktični primeri

analysis: • Scattered plot • Radar plot • Polar plot • Multidimensional scaling

Introduction to multivariate analysis: • Data preprocessing • Multinormal distribution • Normalisation • Generating hypotheses

Overview of multivariate analysis methods: • MANOVA • Covariance • Cluster analysis • Linear regression • Logistic regression

Practical examples


1. Field A.: discovering Statistics Using SPSS, Third Edition, Sage Publications Ltd, 2009. 2. Warren J. Ewens, Gregory R. Grant: Statistical Methods in Bioinformatics: An Introduction, Second

Edition. Springer Verlag, New York 2005. 3. IBM SPSS Statistics Baze 24, IBM, 2016, Dosegljivo na:

ftp://public.dhe.ibm.com/software/analytics/spss/documentation/statistics/24.0/en/client/Manuals/IBM_SPSS_Statistics_Base.pdf

4. Alexander Isaev: Introduction to Mathematical Methods in Bioinformatics. Springer, 2004.

Cilji in kompetence: Objectives and competences:

Ponoviti osnovne statistične metode,

Prikazati različne grafične predstavitve podatkov za multivariatno analizo,

Podati pregled multivariatnih metod,

Naučiti študente izbire ustrezne metode za statistično analizo podatkov,

Prikaz uporabe na nekaterih tipičnih primerih iz mikrobiologije.

Študentje bodo največkrat znali uporabiti primerno metodo multivariatne statistične analize glede na dani problem.

Pridobljeno znanje bodo rutinirano uporabljali tako med študijem kot tudi pri kasnejšem delu.

Izkušnje, pridobljene z implementacijo in študijem delovanja v mnogih splošnih primerih, bodo znali uporabiti v konkretnih praktičnih aplikacijah s področja bioinformatike.

Refresh knowledge of basic statistical methods,

Show different data representations for multivariate analysis,

Give overview of multivariate methods,

Teach students which statistical analysis method to choose,

Demonstrate usage of some methods on microbiology cases.

Students should know which multivariate statistical method to use in a given case.

Gained knowledge will be routinely used in their future work.

Experience gathered here will be aplicable to actual real world cases from the field of bioinformatics.






se bodo zavedali pomena priprave in analize podatkov ter izbire ustrezne metode za statistično analizo glede na postavljeno hipotezo

spoznali bodo različne možnosti grafične predstavitve podatkov,

spoznali bodo različne porazdelitve in najpogostejše načine normalizacije podatkov,

spoznali bodo najpogosteje uporabljene metode multivariatne analize,

pridobljeno znanje bodo znali praktično uporabiti pri reševanju problemov s področja bioinformatike

Knowledge and understanding: Students:

Should know how to preprocess and analyse data and how to determine an appropriate method according to hypothesis set

will find out about different graphical data representations

will find out about different distributions and common normalisation approaches,

will gain knowledge about most widely used multivariate analysis methods,

should know how to practically use gained knowledge for solving problems in the field of bioinformatics.



Predavanja, razgovor, demonstracija, avditorne vaje, računalniške vaje.

Lectures, discussion, demonstration, theoretical exercises, computer exercises



Assessment:


Naloge (računalniške vaje)

individualni projekt.

20 80


coursework (practical assignments)

individual project.


DINEVSKI, Dejan, POVALEJ, Petra, KRAVOS, Matej. Intelligent data analysis for the diagnosis of alcohol dependence syndrome. Journal of international medical research, ISSN 0300-0605, 2011, vol. 39, no. 3, str. 988-1000. [COBISS.SI-ID 512129848] POVALEJ, Petra, GALLEGO, J.A., ROMERO, J. P., GLASER, Vojko, ROCON, E., BENITO-LEÓN, Julián, BERMEJO-PAREJA, Félix, POSADA, Ignacio J., HOLOBAR, Aleš. New perspectives for computer-aided discrimination of Parkinson's disease and essential tremor. Complexity, ISSN 1099-0526. [Online ed.], 2017, vol. 2017, no. 4327175, 1-17 str., ilustr., graf. prikazi. https://www.hindawi.com/journals/complexity/2017/4327175/, doi: 10.1155/2017/4327175. [COBISS.SI-ID 2368420] 2. POVALEJ, Petra, OBRADOVIĆ, Zoran, ŠTIGLIC, Gregor. Contribution of temporal data to predictive performance in 30-day readmission of morbidly obese patients. PeerJ, ISSN 2167-8359, 2017, vol. 5, no. 3230, str. 1-14, graf. prikazi. https://peerj.com/articles/3230/, https://dk.um.si/IzpisGradiva.php?id=67104, doi: 10.7717/peerj.3230. [COBISS.SI-ID 2321060] POVALEJ, Petra, GALLEGO, J.A., FARINA, Dario, HOLOBAR, Aleš. On repeatability of motor unit characterization in pathological tremor. V: PONS, José L. (ur.), TORRICELLI, Diego (ur.), PAJARO, Marta (ur.). Converging clinical and engineering research on neurorehabilitation, International Conference on Neurorehabilitation, ICNR 2012, Toledo, Spain, November 14-16, 2012, (Biosystems & Biorobotics, ISSN 2195-3562). Heidelberg [etc.]: Springer, cop. 2013, part 1, str. 553-556, ilustr. [COBISS.SI-ID 16456214] POVALEJ, Petra, KANIČ, Vojko, KOKOL, Peter. Determining risk factors for survival after LMCA stenosis with intelligent data analysis. Computers in cardiology, ISSN 0276-6574, vol. 34, 2007, str. 53-56, ilustr. [COBISS.SI-ID 1352356]


Predmet: Osnove molekularne in celične biologije

Course title: Basics of molecular and cell biology




Semester Semester



Bioinformatics 1 1



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial


work



ECTS

30 30 90 6

Nosilec predmeta / Lecturer: Doc. dr. Saška Lipovšek Delakorda

Jeziki / Languages:




Prerequisits:

Vsebina:


DNA struktura in lastnosti, replikacija (prokarionti, eukarionti), rekombinacija DNA, DNA popravljalni mehanizmi, DNA mutacije, struktura kromosomov. RNA struktura in lastnosti, vrste RNA molekul in funkcije, transkripcija (prokarionti, eukarionti), postranskripcijske modifikacije. Struktura proteinov, sinteza proteinov, posttranslacijske modifikacije proteinov, zvijanje proteinov, transport proteinov. Regulacija proteinske sinteze: regulacija ekspresije genov pri prokariontih, pri bakteriofagih, pri evkariotskih organizmih (enoceličnih, multicelularnih, povezava z embrionalnim razvojem), regulacija na ravni translacije in posttranslacijska regulacij., Embrionalni razvoj. Celična delitev (mejoza, mitoza). Celični cikel, proliferacija, diferenciacija celic, apoptoza.

DNA structure and characteristics, replication (prokaryotes, eukaryotes), recombination, repair and mutations,, structure and function of genes and chromosomes. RNA structure characteristics: role of different types of RNA, transcription (prokaryotes, eukaryotes), post transcription modification. Protein structures, synthesis of proteins, translation, posttranslational modifications, protein folding, protein trafficking. Regulation of protein synthesis: transcriptional regulation of gene expression,, regulation of translation, posttranslational regulation . Embryonic development. Cell division (meiosis, mitosis). Cell cycle: proliferation, differentiation, apoptosis. Integration of cells into tissues, communication between cells, signal transduction, receptors, hormone signaling.

Povezovanje celic v tkiva, komunikacija med celicami, signalne poti, receptorji, hormoni. Imunski sistem. Virusi, HIV, SARS, DNA diagnostika pri infekcijskih boleznih.

Immune system. Viruses :HIV, SARS, Avian influence, DNA diagnostics and infection diseases.


1. B. ALBERTS et al.: Molecular biology of the cell., 4th Ed., Gerland Publish, Inc., New York, 2002 2. LODISH H., Baltimore D., Berk A., Zipursky S.L., Matsudaira P., Darnell J.: Molecular Cell Biology, 5th

Ed., Scientific American Books, Freeman and Co., New York, 2004 3. Bruce Alberts, Dennis Bray, Karen Hopkin, Alexander Johnson, Julian Lewis, Martin Raff, Keith Roberts,

Peter Walter: Essential cell biology, 2nd Ed., Gerland Publish, Inc., New York, 2003



Predmet bo nudil študentom osnovno razumevanje in celostni pristop k osnovnim molekularnim procesom v celici, tkivih, organih in celotnem organizmu. Poudarek bo na prenosu DNA informacije za sintezo proteinov.

Students will understand basic molecular mechanisms in the cell, how cells are organized in tissues, organs and whole organisms. The focus will be on transfer of genomic information to synthesis of proteins.



Znanje in razumevanje: osnovne molekularne procese v celici

Knowledge and understanding: basic molecular processes in the cell



Predavanja

Seminarske vaje

Lectures

Tutorial



Assessment:


pisni in

ustni izpit 60 40


writen and

oral exemination


The EVIDENCE on the degradation processes in the midgut epithelial cells of the larval antlion Euroleon nostras (Geoffroy in Fourcroy, 1785) (Myrmeleontidae, Neuroptera) [Elektronski vir] / Saška Lipovšek ... [et al.]. - Ilustr. - Nasl. z nasl. zaslona. - Opis vira z dne 27. 3. 2012. - Soavtorji: Ilse Letofsky-Papst, Ferdinand Hofer, Gerd Leitinger, Dušan Devetak. - Bibliografija: str. 664-665. - Abstract. V: Micron. - ISSN 0968-4328.. - Vol. 43, iss. 5 (2012), str. 651-665. . - doi: 10.1016/j.micron.2011.11.012 COBISS.SI-ID 18855176, JCR, WoS, št. citatov do 6. 5. 2012: 0, brez avtocitatov: 0, normirano št. citatov: 0 APPLICATION of analytical electron microscopic methods to investigate the function of spherites in the midgut of the larval antlion Euroleon nostras (Neuroptera: Myrmeleontidae) [Elektronski vir] / Saška Lipovšek ... [et al.]. - Ilustr. - Nasl. z nasl. zaslona. - Opis vira z dne 27. 3. 2012. - Soavtorji: Ilse Letofsky-

Papst, Ferdinand Hofer, Maria Anna Pabst, and Dušan Devetak. - Bibliografija: str. 406-407. - Abstract. V: Microscopy research and technique. - ISSN 1059-910X.. - Vol. 75, iss. 4 (2012), str. 397-407. . - doi: 10.1002/jemt.21069 COBISS.SI-ID 18638856, JCR, WoS, št. citatov do 8. 5. 2012: 1, brez avtocitatov: 0, normirano št. citatov: 0 DUALITY of terrestrial subterranean fauna / Tone Novak ... [et al.]. - Soavtorji: Matjaž Perc, Saška Lipovšek and Franc Janžekovič. - Bibliografija: str. 62-64. - Abstract. V: International journal of speleology. - ISSN 0392-6672.. - Vol. 41, no. 2 (2012), str. 181-188. . - doi: 10.5038/1827-806X.41.2.5 COBISS.SI-ID 19061512, JCR


Predmet: Podatkovno rudarjenje in iskanje novega znanja

Course title: Data mining and knowledge discovery




Semester Semester



Bioinformatics 1 2



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial


work



ECTS

30 30 90 6

Nosilec predmeta / Lecturer: Red. prof. dr. Milan Zorman, Red. prof. dr. Vili Podgorelec, Izr. prof. dr. Boštjan Brumen

Jeziki / Languages:




Prerequisits:

Osnovno poznavanje dela z računalnikom: delo z miško, tipkovico, poznavanje okolja Windows, dela s preglednicami (MS Excel) Osnove računalništva v bioinformatiki

Basic computer user skills: working with mouse, keyboard, MS Windows operating system, spreadsheets (MS Excel)

Computer Science for Bioinformatics

Vsebina: Content (Syllabus outline):

Uvod v inteligentne sisteme

Osnove zbirk podatkov

Priprava podatkov

Delo z manjkajočimi podatki

Metode nadzorovanega strojnega učenja: o Odločitvena drevesa o Nevronske mreže o Grobe množice o Hibridne metode

Evalvacija pridobljenega znanja

Introduction to inteligent systems

Basics of data sets

Data preprocessing

Working with missing data

Methods for supervised machine learning: o Decision trees o Neural networks o Rough sets o Hybrid methods

Evaluation of acquired knowledge

Temeljna literatura in viri / Readings:

- Zorman Milan, Podgorelec Vili, Lenič Mitja, Povalej Petra, Kokol Peter in Tapajner Alojz: Inteligentni sistemi in profesionalni vsakdan, Univerza v Mariboru, Center za Interdisciplinarne in multidisciplinarne raziskave in študije UM, Maribor, 2003

- J. Han, M. Kamber: Data Mining: Concepts and Techniques, Second Edition, Elsevier, Morgan Kaufmann Publishers, 2006.

- I. H. Witten, E. Frank, M. A. Hall: Data Mining, Practical Machine Learning Tools and Techniques, Third Edition, Morgan Kaufmann Publishers, 2011.

- spletni viri / internet sources

Cilji in kompetence: Objectives and competences:

Seznaniti študente s postopki iskanja novega znanja v bazah podatkov.

Naučiti študente dela z inteligentnimi metodami za avtomatski zajem in evaluacijo znanja iz podatkovnih zbirk.

To introduce students to knowledge acquisition from data sets.

To teach students about intelligent methods for automatic acquisition and evaluation of knowledge.




Zajemanja podatkov

Shranjevanja podatkov

Priprave podatkov za obdelavo z inteligentnimi metodami

Osnov in uporabe inteligentnih metod

Evalvacije rezultatov inteligentnih metod

Uporabe pridobljenega znanja.

Sposobnost učinkovitejšega zajema, shranjevanja in uporabe podatkov.

Znanje za uporabo podatovnega rudarjenja in iskanja novega znanja na poljubnih področjih.

Poznavanje inteligentih metod.

Knowledge and understanding:

Data acquisition

Storing data.

Data preprocessing for analysis with intelligent methods.

Basics and usage of intelligent methods.

Evaluation of results of intelligent methods.

Usage of acquired knowledge.

Capability to more efficiently acquire, store and use data.

Knowledge about data mining and knowledge acquisition in various areas.

Familiarity with intelligent methods.




Lectures, discussion, demonstration, computer exercises



Assessment:


- Naloge (računalniške vaje) - pisni izpit, - ustni izpit.

20 30 50


- coursework (practical assignments) - written examination (can be

achieved also with two non obligatory colloquia),

- oral examination.


ZORMAN, Milan Classification of follicular lymphoma images : a holistic approach with symbol-based machine learning

methods / Milan Zorman, José Luis Sánches de la Rosa, Dejan Dinevski. - Graf. prikazi. - Abstract ; Zusammenfassung. - Bibliografija: str. 708-709. V: Wiener Klinische Wochenschrift. - ISSN 0043-5325.. - Jg. 123, Heft 23/24 (2011), str. 700-709. COBISS.SI-ID 15706134, JCR ZORMAN, Milan Opening the knowledge tombs - web based text mining as approach for re-evaluation of machine learning rules / Milan Zorman, Sandi Pohorec and Boštjan Brumen. - Abstract. - Bibliografija: str. 542. V: Lecture notes in computer science. - ISSN 0302-9743. - Vol. 6295 (2010), str. 533-542. COBISS.SI-ID 14444310 ZORMAN, Milan Explanatory approach for evaluation of machine learning-induced knowledge / M. Zorman and M. Verlič. - Abstract. - Bibliografija: str. 1550-1551.V: Journal of international medical research. - ISSN 0300-0605.. - Letn. 37, št. 5 (2009), str. 1543-1551. COBISS.SI-ID 13645334, JCR PODGORELEC, Vili, 1972- Taking advantage of education data : advanced data analysis and reporting in virtual learning environments / V. Podgorelec, S. Kuhar. - Bibliografija: str. 116. - Abstract. V: Elektronika ir elektrotechnika. - ISSN 1392-1215.. - Nr. 8 (2011), str. 111-116. COBISS.SI-ID 15441174, JCR, WoS, št. citatov do 6. 5. 2012: 0, brez avtocitatov: 0, normirano št. citatov: 0 PODGORELEC, Vili, 1972- Supporting the study process using semantic web technologies / V. Podgorelec, M. Gresak. - . - Dostopno tudi na: http://www.ee.ktu.lt/journal/2011/10/23__ISSN_1392-1215_Supporting%20the%20Study%20Process%20using%20Semantic%20Web%20Technologies.pdf. - Bibliografija: str. 108. - Abstract.V: Elektronika ir elektrotechnika. - ISSN 1392-1215.. - No. 10 (2011), str. 105-108. COBISS.SI-ID 15625238, JCR, WoS, št. citatov do 11. 4. 2012: 0, brez avtocitatov: 0, normirano št. citatov: 0 PODGORELEC, Vili, 1972- Expert-assisted classification rules extraction algorithm / Vili Podgorelec. - Abstract. - Bibliografija: str. 462.V: Lecture notes in computer science. - ISSN 0302-9743. - Vol. 6295 (2010), str. 450-462. COBISS.SI-ID 14444566 ASSESSMENT of classification models with small amounts of data / Boštjan Brumen ... [et al.]. - Soavtorji: Matjaž B. Jurič, Tatjana Welzer, Ivan Rozman, Hannu Jaakkola, Apostolos Papadopoulos. V: Informatica. - ISSN 0868-4952.. - Vol. 18, no. 3 (2007), str. 343-362. COBISS.SI-ID 11983638, JCR, WoS, št. citatov do 10. 2. 2010: 3, brez avtocitatov: 3, normirano št. citatov: 3 ZORMAN, Milan Opening the knowledge tombs - web based text mining as approach for re-evaluation of machine learning rules / Milan Zorman, Sandi Pohorec and Boštjan Brumen. - Abstract. - Bibliografija: str. 542.V: Lecture notes in computer science. - ISSN 0302-9743. - Vol. 6295 (2010), str. 533-542. COBISS.SI-ID 14444310 JEREB, Borut, 1962- Upravljanje IT tveganj s pomočjo Risk IT [Elektronski vir] / Borut Jereb, Boštjan Brumen. - ilustr. - Sekcija UI: Upravljanje informatike / IT governance. - Nasl. pri prispevku. - Bibliografija: str. 14. V: Uravnotežite naložbe, tveganja in razvoj za uspeh [Elektronski vir] / Dnevi slovenske informatike 2010 - DSI, Portorož, Slovenija, 14.-16. april 2010. - Ljubljana : Slovensko društvo Informatika, 2010. - ISBN 978-961-6165-32-7. - 14 str. COBISS.SI-ID 512183357


Predmet: Računalniška geometrija za bioinformatiko

Course title: Computational geometry for bioinformatics




Semester Semester



Bioinformatics 1 2



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial

Lab. vaje Laboratory work



ECTS

30 30 90 6

Nosilec predmeta / Lecturer: Prof. dr. Borut Žalik

Jeziki / Languages:




Prerequisits:

Potrebna so osnovna programerska znanja. Zaželeno je tudi poznavanje temeljnih znanj bioinformatike, analitične geometrije in linearne algebre (razdalja, ploščina, prostornina, skalarni in vektorski produkt).

Basic programming skills are required. In addition, the basic understanding of bioinformatics, analytical geometry and linear algebra are recommended (distances, surfaces, volume, scalar and vector product).

Vsebina:


Uvod (pomen in pomen geometrijskih struktur v bioinformatiki)

Izbočena lupine o Algoritmi za konstrukcijo (naivni

pristop, Jarvishev pristop, Grahamov preiskovanje, inkrementalna metoda, metoda s prebirno premico, hitra izbočena lupine)

o Uporaba izbočenih lupin pri preslikavah PSIMAP

Problem najbližje točke o enakomerna delitev ravnine, o spiralni algoritem o statičen in dinamičen problem

Introduction (Importance of geometric structures in bioinformatics)

Convex hulls o Algorithms for the convex hull

construction (brute force, Jarvish’s approach, Graham’s scan, incremental method, sweep-line-based approach, quickhull)

o Use of convex hull in PSIMAP algorithms

The closest point problem o uniform plane subdivision, o spiral algorithm o static and dynamical problem o Frenet distance (protein backbone

o Frenetova razdalja (konstrukcija proteinske hrbtenice)

o iskanje najbližjih k-parov v velikih množicah nepreciznih točk - proteinov

Triangulacija (definicija, lastnosti, MWT, Hammiltonova triangulacija, Delaunayeva triangulacija)

o Algoritmi za konstrukcijo Delaunayeve triangulacije (naključni inkrementalni algoritmi, algoritem s prebirno premico)

o Delaunayeva tetrahedrizacija o Aplikacija Delaunayeve

tetrahedrizacije na spremembo oblik in položaja proteinov.

Voronoiev diagram (definicija, lastnosti) o Algoritmi za konstrukcijo

Voronoievih diagramov (naivni pristop, naključni inkrementalni pristop, Fortunov pristop)

o Določitev površja molekul iz Voronoievih diagramov

o Določitev prostornine proteinov.

Vsota Minkovskega o Konstrukcija vsote Minskovskega

nad točkami in daljicami o Aplikacija vsote Minkovskega na

van der Waalsove lupine

construction) o closest k-pair search in large sets of

imprecise points - proteins

Triangulation (definition, characteristics, MWT, Hammilton triangulation, Delaunay triangulation)

o Algorithms for Delaunay triangulation construction (random incremental algorithms, sweep-line algorithms)

o Delaunay tetrahedronisation o Application of Delaunay

tetrahedronisation for shape in position transformations of proteins.

Voronoi diagram (definition, properties) o Algorithms for Voronoi diagram

construction (brute force, Fortune’s approach)

o Molecular surface determination from the Voronoi diagrams

o Determination of proteins’ volume

Minkowski’s sum o Minkowski’ sum construction on

points and line segments o Application of Minkowski’ sum: van

der Waals’ hull

Collision detection o Method with hierarchically

organised bounding boxes and spheres; method with dimension reduction


1. M. de Berg, M. van Kreveld, M.Overmars, O. Schwarzkopf, Computational Geometry - Algorithms and Applications, Springer 1997.

2. F. P. Preparata, M. I. Shamos, Computational Geometry: An Introduction, Springer Verlag, 1985. 3. J. O'Rourke, Computational Geometry in C, Cambridge University Press, 1998. 4. N. C. Jones, P. A. Pevzner, An Introduction to Bioinformatics Algorithms, The MIT Press, 2004.



Študent pridobi znanje o pomenu računalniške geometrije in njene uporabnosti v bioinformatiki. Spozna ključne probleme obdelave velikih količin geometrijskih podatkov in pospešitvene tehnike za njihove učinkovite rešitve. Zna povezovati obstoječa znanja računalniške geometrije in jih aplicirati na probleme v bioinformatiki. Pozna učinkovite in stabilne algoritme računalniške geometrije, ki rešujejo naloge iz bioinformatike.

A student gets the knowledge about the importance of computational geometry and its applicability in bioinformatics. He/she recognises key problems in processing large amounts of geometric data, and acceleration techniques, dealing efficiently with these problems. He/she knows to link existing knowledge of computational geometry and apply it to the problems in bioinformatics. He knows efficient and stable algorithms of computational geometry, solving tasks from the field of

bioinformatics.




o znajo poiskati izbočeno lupino množice točk in jo uporabiti pri preslikavi PSIMAP,

o poznajo problem najbližje točke in obstoječe rešitve ter skonstruirati proteinske hrbtenice na podlagi Frenetovih razdalj,

o poznajo različne vrste triangulacij, o poznajo algoritme konstrukcije

Delaunayeve triangulacije, o poznajo aplikacije Delaunayeve

triangulacije v biomedicini, o poznajo Voronoieve diagrame, o znajo določiti površino in prostornino

molekul razvrščenih v Voronoieve strukture,

o poznajo vsoto Minkowskega in algoritme za njihovo konstrukcijo,

o znajo razširiti vsoto Minkowskega na Van der Waalsove lupine

Ključne spretnosti: - znajo preslikati probleme iz bioinformatike v že rešene probleme računalniške geometrije, - znajo izbrati ustrezne algoritme za geometrijske probleme iz bioinformatike, - pridobijo spretnosti pri implementaciji geometrijskih algoritmov (zaokrožitvene napake, propagacija napak).

Knowledge and understanding: Students:

o get knowledge to find the convex hull for a set of points, and to use it in PSIMAP algorithms,

o they recognize the closests point problem and existing solutions. They know how construct the protein backbone by using Frenet’s distance

o they know different kinds of triangulation o they know algorithms for Delaunay

triangulation construction, o they know applications of Delaunay

triangulation in bioinformatics o they know Voronoi diagrams o they are able to determine the surface and

the volume of molecules, organised in Voronoi structures

o they know Mikowski’s sum and the algorithms for its construction

o they know how to generalise the Mikowski’s sum,

o to Van der Waals’ hulls Key skills: o they know how to translate problems from the bioinformatics into already solved problems of computational geometry, o they know to select appropriate algorithm for geometrical problems in bioinformatics, o they get skills for implementing geometric algorithms (rounding error, error propagation).



Razlaga, razgovor, demonstracija, računalniške vaje Explanation, discussion, demonstration, computer exercises



Assessment:

Način (pisni izpit, ustno izpraševanje, naloge, projekt) Ustno izpraševanje, domače naloge, računalniške vaje

50 % 20 % 30 %

Type (examination, oral, coursework, project): oral examination, homework, computer exercises.


1. ŠPELIČ, Denis, ŽALIK, Borut. Lossless compression of threshold-segmented medical images. Journal of medical systems, Published online: 15 April 2011, doi: 10.1007/s10916-011-9702-5. 2. ZADRAVEC, Mirko, BRODNIK, Andrej, MANNILA, Markus, WANNE, Merja, ŽALIK, Borut. A practical approach to the 2D incremental nearest-point problem suitable for different point distributions. Pattern recognition, Vol. 41, No. 2, 2008, pp. 646-653. 3. KLAJNŠEK, Gregor, ŽALIK, Borut. Progressive lossless compression of volumetric data using small memory load. Computerized medical imaging and graphics, Vol. 29, No. 4, 2005, pp. 305-312.


Predmet: UPORABNO RAČUNALNIŠTVO ZA BIOINFORMATIKO

Course title: APPLIED COMPUTER SCIENCE IN BIOINFORMATICS




Semester Semester



Bioinformatics 1 2



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial


work



ECTS

30 30 90 6

Nosilec predmeta / Lecturer: Red. prof. dr. Milan Zorman

Jeziki / Languages:




Prerequisits:

Osnovno poznavanje dela z računalnikom: delo z miško, tipkovico, poznavanje okolja Windows.

Basic computer user skills: working with mouse, keyboard, MS Windows operating system.

Vsebina:


Urejevalniki besedil, napredno – MS Word

Delo s preglednicami, napredno – MS Excel

Delo z bazami podatkov - MS Access o Relacijski model o Vnosne forme o Povpraševanje o Kreiranje poročil

Iskalniki po svetovnem spletu

Bibliografske baze podatkov

Delo s statističnimi orodji - RStudio

Word processors, advanced – MS Word

Spreadsheets, advanced – MS Excel

Working with data bases - MS Access o Relational model o Entry forms o Querying o Creating reports

Internet searchers

Bibliographic data bases

Statistical tools – RStudio


Dan Gookin: Word 2003 for Dummies, Wiley publishing, 2003.

Greg Harvey: Excel 2003 for Dummies, Wiley publishing, 2003.

John Kaufeld: Access 2003 for Dummies, Wiley publishing, 2003.

spletni viri / internet sources



- predstaviti študentom osnove uporabnega računalništva

- naučiti študente dela z urejevalniki besedil - naučiti študente dela s preglednicami - naučiti študente dela z bazami podatkov - predstaviti študentom iskalnike po svetovnem

spletu - naučiti študente uporabe bibliografskih baz

podatkov - naučiti študente dela z naprednimi statističnimi

orodji

- introduce students to applied computer science - to teach students how to use word processors - to teach students how to use spreadsheets - to teach students usage of databases - introduce students to internet searchers - to teach students how to use bibliographic data

bases - to teach students how to use advanced

statistical tools



Znanje in razumevanje: - osnov uporabnega računalništva - dela z urejevalniki besedil - dela s preglednicami - osnove dela z bazami podatkov - uporaba računalnika kot uporabnega

pripomočka pri reševanju vsakodnevnih nalog - dvig učinkovitosti pri opravljanju dela

Knowledge and understanding: - of basics of applied computer science, - of word processors, - of spreadsheets, - of database basics, - of internet searchers, - basics of bibliographic data bases - using computer for solving problems in everday

professional situations - improved efficiency



Predavanja, razgovor, demonstracija, avditorne vaje, računalniške vaje.

Lectures, discussion, demonstration, theoretical exercises, computer exercises



Assessment:

Način (pisni izpit, ustno izpraševanje, naloge, projekt) - naloge (računalniške vaje) - pisni izpit (mogoče ga je opraviti tudi z dvema neobveznima kolokvijema), - ustni izpit.

30% 50%

20%

Type (examination, oral, coursework, project): - coursework (practical assignments) - written examination (can be achieved also with two non obligatory colloquia), - oral examination.


ZORMAN, Milan Classification of follicular lymphoma images : a holistic approach with symbol-based machine learning methods / Milan Zorman, José Luis Sánches de la Rosa, Dejan Dinevski. - Graf. prikazi. - Abstract ; Zusammenfassung. - Bibliografija: str. 708-709. V: Wiener Klinische Wochenschrift. - ISSN 0043-5325.. - Jg. 123, Heft 23/24 (2011), str. 700-709. COBISS.SI-ID 15706134, JCR ZORMAN, Milan Opening the knowledge tombs - web based text mining as approach for re-evaluation of machine learning rules / Milan Zorman, Sandi Pohorec and Boštjan Brumen. - Abstract. - Bibliografija: str. 542. V: Lecture notes in computer science. - ISSN 0302-9743. - Vol. 6295 (2010), str. 533-542. COBISS.SI-ID 14444310

ZORMAN, Milan Explanatory approach for evaluation of machine learning-induced knowledge / M. Zorman and M. Verlič. - Abstract. - Bibliografija: str. 1550-1551.V: Journal of international medical research. - ISSN 0300-0605.. - Letn. 37, št. 5 (2009), str. 1543-1551. COBISS.SI-ID 13645334, JCR


Predmet: Uvod v bioinformatiko

Course title: Introduction to bioinformatics




Semester Semester



Bioinformatics 1 2



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial




ECTS

30 30 90 6

Nosilec predmeta / Lecturer: prof. dr. Uroš Potočnik

Jeziki / Languages:




Prerequisits:

Poznavanje osnov molekularne biologije, biokemije in molekularne genetike

Understanding basics of molecular biology, biochemistry and molecular genetics

Vsebina:


Podatkovne zbirke v molekularni biologiji in genomiki:

- indeksiranje in iskalni profili, - Bibliografske podatkovne zbirke (PubMed), - tekstovne podatkovne zbirke (OMIM), - faktografske podatkovne zbirke ( DNA

sekvence (Genbank), genomov, proteinske sekvence (SwissProt), proteinske structure, ekspresijke, metabolne poti,

- Integrirani sistemi za dostop do podatkovnih zbirk: Entrez (NCBI), ExPASy , Ensembl

Sekvenčne poravnave in konsktrukcija filogenetskih dreves: merila sekvenčne podobnosti, poravnava dveh zaporedij, poravnava večih zaporedij, iskanje podobnih zaporedij v podatkovnih zbirkah (skriti modeli Markov, PSI-Blast, profile), filogenetska drevesa (metoda klastrov, klad, problem različnih

Databases in molecular biology and genomics: - database indexing and search profiles - bibliographic databases (PubMed) - text databases (OMIM) - surveys of molecular biology databases and

servers: nucleotide acid sequence databases (GenBank), genome databases, protein sequence databases (Swiss Prot), databases of structures, expression databases, databases of metabolic pathways

- Integrated systems for data retrieving: ENTREZ (NCBI), ExPASy, Ensembl

Sequence alignments and phylogenetic trees: measures of similarity, computing the alignment of two sequences, multiple sequence alignments (profiles, PSI-BLAST, Hidden Markov Models), phylogenetic trees (clustering methods, cladistic method, the problem of varying rates of evolution)

stopenj evolucije). Proteinske strukture in odkrivanje novih zdravil: zvijanje in stabilnost proteinske strukture, superpozicija struktur in strukturne poravnave, klasifikacija proteinskih struktur, predikcija strukture in modeliranje, povezava proteinske strukture z genomom, predikcija funkcije proteinov (ortologi, paralogi), računalniško načrtovanje novih zdravil.

Protein structure and drug discovery: protein stability and folding, superposition of structures and structural alignments, evolution of protein structures, classification of protein structures, protein prediction and modeling, assignment of protein structures to genomes, drug discovery and development, computer-assisted drug design


1. Lesk A: (2005) Introduction to Bioinformatics. 2nd Ed, Oxford University Press, Oxford, UK 2. Barnes MR, Gray IC: Bioinformatics for geneticist. John Wiley&Sons, R.J.M , West Sussex, 2003. 3. Attwood TK, Parry-Smith DJ (1999) Introduction to Bioinformatics. Prentice Hall, Harlow, England. 4. Baxevanis AD, Francis Ouellette BF (1998) Bioinformatics A Practical Guide to the Analysis of Genes

and Proteins. Wiley-Interscience, A John Wiley & Sons Inc., Publication, New York, USA. 5. Higgins D, Taylor W (2000) Bioinformatics. Sequence, Structure and Databanks. Oxford University

Press, Oxford, UK. 6. Kanehisa M (2002) Post-genome Informatics. Oxford University Press, Oxford, United Kingdom



Študentom pregledno predstaviti glavne podatkovne zbirke in programska orodja s področja biokemije, molekularne biologije in genomike. Študenti bodo znali uporabljati programska orodja za dostop do relevantnih podatkov iz podatkovnih zbirk s področja molekularne biologije in genomike.

Students will be provided with comprehensive review of the most relevant databases and bioinformatic tools in the fields of biochemistry, molecular biology and genomics. Students will be able to access and retrieve most relevant data from available databases in the field of molecular biology and genomics.




vrste in struktura podatkovnih zbirk

pomen in interpretacija molekularno bioloških in genomskih podatkov


type and structure of databases

meaning and interpretation of molecular biology and genomic data



Predavanja

Seminarske vaje

Lectures

Tutorial



Assessment:


pisni in

ustni izpit

60 40


writen and

oral exemination


POTOČNIK, Uroš, 1969- Trenutna komercializacija osebne genetske analize-zanesljiva napoved tveganja za pogoste kompleksne bolezni ali zavajanje potrošnikov? [Elektronski vir] = Current commercialization of personal genetic analysis-reliable prediction of susceptibility to common complex diseases or misleading of the consumers? / Uroš Potočnik. - Povzetek ; Abstract. - Bibliografija: str. 4-5. V: Slovenski kemijski dnevi 2011, Portorož, 14-16 september 2011 [Elektronski vir] / [organizirala] Fakulteta za kemijo in kemijsko tehnologijo, Univerza v Mariboru [v sodelovanju s Slovenskim kemijskim društvom ... et al.]. - Maribor : FKKT, 2011. - ISBN 978-961-248-289-3. - 5 str. COBISS.SI-ID 15319318 ŠIMENC, Janez, 1973- Rapid differentiation of bacterial species by high resolution melting curve analysis / J. Šimenc and U. Potočnik. - Abstract. - Bibliografija: str. 262-263.V: Applied biochemistry and microbiology. - ISSN 0003-6838.. - Vol. 47, no. 3 (2011), str. 256-263. . - doi: 10.1134/S0003683811030136 COBISS.SI-ID 14937622, JCR, WoS, št. citatov do 11. 4. 2012: 1, brez avtocitatov: 1, normirano št. citatov: 0 A CYP17A1 gene polymorphism in association with multiple uterine leimyomas; a meta-analysis / Maja Pakiz ... [et al.]. - Soavtorji: Uros Potocnik, Igor But, Faris Mujezinovic. - Bibliografija: str. 33-34. – Abstract V: Disease markers. Section A, Cancer biomarkers. - ISSN 1574-0153.. - Vol. 8, no. 1 (2010/2011), str. 29-34. . - doi: 10.3233/DMA-2011-0817 COBISS.SI-ID 4033599, JCR, WoS, št. citatov do 6. 10. 2011: 0, brez avtocitatov: 0, normirano št. citatov: 0

2. LETNIK


Predmet: Bioinformatika in genetske raziskave

Course title: Bioinformatics in genetic research




Semester Semester



Bioinformatics 2 3



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial




ECTS

30 30 90 6

Nosilec predmeta / Lecturer: Izr. prof. dr. Uroš Potočnik

Jeziki / Languages:




Prerequisits:

Poznavanje osnov molekularne biologije, biokemije, humane genetike in bioinformatike

Understanding basics of molecular biology, biochemistry, human genetics and bioinformatics

Vsebina:


Odkrivanje in mapiranje bolezenskih genov: - izbor bolnikov in družin -pozicijsko kloniranje in definicija kandidatnega področja, -Analiza genetske vezave: izbira mikrosatelitnih označevalcev, rekombinacijska frakcija, vrednost LOD, dvotočkovno mapiranje, večtočkovno mapiranje, programska orodja (GENEHUNTER) -test prenosa neravnotežja (ang TDT za transmission disequilibrium test) -analiza -asociacijske študije primeri/kontrole -analiza parov sorodnikov -genetske študije iz genomske sekvence: definicija lokusa; identifikacija in eksrakcija genomske sekvence med dvema markerjema; preverjanje integritete genomske sekvence med dvema

Principles and strategies in identifying human disease genes: -patients and families enrolled in the study -positional cloning and definition of candidate region -linkage analysis: selection of microsatellite markers, recombination fraction, LOD score, two-point mapping, multipoint mapping, program tools (GENHUNTER) -sib.pair analysis -transmission disequilibrium test (TDT) -association studies (case:controls), -genetic studies from genome sequence: locus definition, identification and extraction of sequence between two markers, evaluating genome sequence integrity between two markers, definition of known and new genes in the candidate region, candidate

markerjema; definicija znanih in novih genov na sekvenci kandidatnega področja genoma; izbira kandidatnih genov za analizo-povezovanje z biološko in fiziološko funkcijo, ekspresijo genov; identifikacija novih markerjev v kandidatnem področju genoma; načrtovanje panela genetskih markerjev za gensko tipizacijo Identifikacija polimorfizmov enega nukleotida (SNP) in načrtovanje protokola genske tipizacije: identifikacija SNPjev; določitev funkcijskih in biološko pomembnih SNPjev, načrtovanje začetnih oligonukleotidov za reakcijo PCR; validacija rezutatov genske tipizacije; Statistična analiza genotipov in alelov pri bolnikih in kontrolah (Hi2, Fischerjev test): določitev strukture haplotipov (algoritem maksimizacije pričakovanega); genetsko neravnotežje (linkage disequilibrium); mapiranje kvantitativnih lokusov (QTL) Pregled metod odkrivanja mutacij in genske tipizacije polimorfizmov Primeri uspešnega mapiranja bolezenskih genov za monogenske in kompleksne bolezni Načrtovanje, izvajanje in interpretacija genetskih testov; genetsko svetovanje Molekularne tarče za načrtovanje bioloških zdravil

gene selection: molecular and physiological function, expression; using new markers for fine mapping of candidate region, design of panel markers for genotyping Identification on Single nucleotide polymorphisms (SNPs) and genotyping protocol, functional and biological significant SNPs, PC primer design,validation of genotyping data Technology for mutation detection and polymorphism genotyping Statistical analysis of genotype and allele frequency in patients and controls (Hi2, Fischer exact) Haplotype estimation (Expectation maximization algorithm), linkage disequilibrium, Mapping quantitative locus traits (QTL) Examples of successful identification of disease genes in monogenic (Mendel) and complex traits Design, application and interpretation of genetic tests, genetic counseling Molecular targets for drug design


1. Barnes MR, Gray IC: Bioinformatics for geneticist. John Wiley&Sons, R.J.M , West Sussex, 2003. 2. STRACHAN T and READ AP: Human Molecular genetics, Gerland Publish, Inc., New York, 3rd ed.,

2004 3. David J. Balding (Editor), M. Bishop (Editor), C. Cannings (Editor): Handbook of Statistical Genetics,

Second Edition, John Wiley&Sons, , 2003 4. Tekoča periodika



Cilj predmeta je naučiti študente uporabljati razpoložljve podatkovne zbirke in orodja bioinformatike za raziskovanje na področju molekularne genetike in genomike. Študenti bodo seznanjeni z najnovejšimi in najpomembnejšimi dosežki in odkritji na področju humane molekularne genetike ter na možnostih prenosa teh odkritij in znanj v klinično prakso za izboljšanje preprečavenja in diagnosticiranja bolezni, načrtovanje in uporabo molekularnih in bioloških zdravil ter individualiziranemu zdravljenju na osnovi genetskih testov. Poudarek bo na odkrivanju in mapiranju bolezenskih genov ter potencialnih molekularnih tarč za načrtovanje zdravil.

Students will be trained to use available resources, databases and bioinformatics tools for research in the field of molecular genetics and genomics. The aim of this course is to keep the students up to date with the most important discoveries with highest impact in the field of human molecular genetics. The course will address the possibilities of transfer of new discoveries and achievements in the field of genomics, molecular genetics and biomedicine into clinical practice including improved disease prevention and diagnosis, design and application of molecular drugs and personalized medicine. The focus will be on identification and mapping of human disease genes and potential molecular targets for drug design.




metodika mapiranja bolezenskih genov

funkcija in vloga genov v patogenezi bolezni


approaches for identification and mapping of disease gene

gene function and their role in pathogenesis



Predavanja

Seminarske vaje

Lectures

Tutorial



Assessment:


pisni in

ustni izpit

60 40


writen and

oral exemination


POTOČNIK, Uroš, 1969- Trenutna komercializacija osebne genetske analize-zanesljiva napoved tveganja za pogoste kompleksne bolezni ali zavajanje potrošnikov? [Elektronski vir] = Current commercialization of personal genetic analysis-reliable prediction of susceptibility to common complex diseases or misleading of the consumers? / Uroš Potočnik. - Povzetek ; Abstract. - Bibliografija: str. 4-5. V: Slovenski kemijski dnevi 2011, Portorož, 14-16 september 2011 [Elektronski vir] / [organizirala] Fakulteta za kemijo in kemijsko tehnologijo, Univerza v Mariboru [v sodelovanju s Slovenskim kemijskim društvom ... et al.]. - Maribor : FKKT, 2011. - ISBN 978-961-248-289-3. - 5 str. COBISS.SI-ID 15319318

ŠIMENC, Janez, 1973- Rapid differentiation of bacterial species by high resolution melting curve analysis / J. Šimenc and U. Potočnik. - Abstract. - Bibliografija: str. 262-263.V: Applied biochemistry and microbiology. - ISSN 0003-6838.. - Vol. 47, no. 3 (2011), str. 256-263. . - doi: 10.1134/S0003683811030136 COBISS.SI-ID 14937622, JCR, WoS, št. citatov do 11. 4. 2012: 1, brez avtocitatov: 1, normirano št. citatov: 0 A CYP17A1 gene polymorphism in association with multiple uterine leimyomas; a meta-analysis / Maja Pakiz ... [et al.]. - Soavtorji: Uros Potocnik, Igor But, Faris Mujezinovic. - Bibliografija: str. 33-34. – Abstract V: Disease markers. Section A, Cancer biomarkers. - ISSN 1574-0153.. - Vol. 8, no. 1 (2010/2011), str. 29-34. . - doi: 10.3233/DMA-2011-0817 COBISS.SI-ID 4033599, JCR, WoS, št. citatov do 6. 10. 2011: 0, brez avtocitatov: 0, normirano št. citatov: 0


Predmet: DNA mikromreže in analiza ekspresije genov

Course title: DNA micro nets and analyze of expressions of genes




Semester Semester



Bioinformatics 2 3



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial




ECTS

15 45 90 6


Jeziki / Languages:




Prerequisits:



Vsebina:


Regulacija genske ekspresije z vezavo trans delujočih proteinov na cis delujoče regulatorna zaporedja, modifikacija histonov in remodulacija strukture kromatina Alternativna transkripcija in procesiranje posameznih genov Alelno specifična ekspresija: metilacija, DNA vtisnjevanje (imprinting), polimorfizmi v regulatornih zaporedjih Transkriptomika Kemija vezave molekul na površino, priprava biočipov (vezava cDNA in oligo nukleotidnih sond) Statistična analiza ekspresijskih biočipov: načrtovanje eksperimenta, normalizacija, statistika primerjalne analize ekspresije dveh vzorcev, linearni modeli in njihova uporaba pri kompleksnih eksperimentih, kjer primerjamo gensko ekspresijo

Regulation of gene expression: binding of trans-acting proteins to cis elements, modification of histones, chromatine remodeling Alternative transcription and gene processing Allele specific expression: DNA methylation, imprinting, SNPs in regulatory regions Transcriptomics Chemistry of binding to surface, preparation of microarrays (cDNA and oligo probes) Statistical analysis of microarray data: experimental design, normalization issues, Two-sample statistics for differential expression (DE) and multiple testing issues, linear models and its application in analyzing complex gene expression experiments with two or more treatment comparisons, clustering algorithms, cross –validation, functional annotation using Gene Ontology and sequence information

v dveh ali večih situacijah (npr. različni tretmaji celic), postopki za sestavljanje klastrov, validacija podatkov, funkcijsko vrednoteneje z uporabo podatkovnih zbirk Gene ontology in DNA sekvenc Proteinske mikromreže Uporaba mikromrež v diagnostiki, načrtovanju in razvoju novih zdravil

Protein microarrays Application of microarray technology in diagnostics and in drug design and development


1. Statistical Analysis of Gene Expression Microarray Data edited by T.P. Speed. 2003. Chapman & Hall/CRC.

2. Mark Schena: Microarray Analysis, John Willey&Sons, 2003 3. Steen Knudsen: Guide to Analysis of DNA Microarray Data, 2nd Edition, John Willey&Sons 2004



Študentom bodo predstavljene in ovrednotene različne statistične metode za analizo podatkov pridobljenih z mikromrežami (biočipi). Osnovni pristopi analize bodo vključevali: procesiranje in normalizacijo rezultatov, linearni modeli, testiranje večih hipotez, sestavljanje klastrov, predikcija in funkcijsko ovrednotenje na osnovi genske ontologije in genomske sekvence.

This course will introduce, illustrate and evaluate a variety of statistical methods employed in the context of microarray data analysis. Techniques covered correspond to commonly encountered research questions and study designs and include preprocessing/normalization, linear models, multiple hypothesis testing, clustering, discrimination, prediction and annotation with gene ontology and sequence information.




izvedba analize podatkov pridobljenih z ekspresijskimi mikromrežami

odkrivanje in uporaba relevantnih virov (orodij bioinformatike in podatkov o genomu) za lastne analize

analiza podatkov analiz z biočipi, ki so jih izvedli drugi raziskovalci

načrtovanje študij z uporabo mikromrež


Perform microarray data analyses.

Identify and use relevant resources (genomic data and tools) for their own research.

Assess microarray data analyses performed by others.

Design studies using microarray technology.



Predavanja

Seminarske vaje

Lectures

Tutorial



Assessment:


pisni in

ustni izpit 60 40


writen and

oral exemination


POTOČNIK, Uroš, 1969- Trenutna komercializacija osebne genetske analize-zanesljiva napoved tveganja za pogoste kompleksne bolezni ali zavajanje potrošnikov? [Elektronski vir] = Current commercialization of personal genetic analysis-reliable prediction of susceptibility to common complex diseases or misleading of the consumers? / Uroš Potočnik. - Povzetek ; Abstract. - Bibliografija: str. 4-5. V: Slovenski kemijski dnevi 2011, Portorož, 14-16 september 2011 [Elektronski vir] / [organizirala] Fakulteta za kemijo in kemijsko tehnologijo, Univerza v Mariboru [v sodelovanju s Slovenskim kemijskim društvom ... et al.]. - Maribor : FKKT, 2011. - ISBN 978-961-248-289-3. - 5 str. COBISS.SI-ID 15319318 ŠIMENC, Janez, 1973- Rapid differentiation of bacterial species by high resolution melting curve analysis / J. Šimenc and U. Potočnik. - Abstract. - Bibliografija: str. 262-263.V: Applied biochemistry and microbiology. - ISSN 0003-6838.. - Vol. 47, no. 3 (2011), str. 256-263.. - doi: 10.1134/S0003683811030136COBISS.SI-ID 14937622, JCR, WoS, št. citatov do 11. 4. 2012: 1, brez avtocitatov: 1, normirano št. citatov: 0 A CYP17A1 gene polymorphism in association with multiple uterine leimyomas; a meta-analysis / Maja Pakiz ... [et al.]. - Soavtorji: Uros Potocnik, Igor But, Faris Mujezinovic. - Bibliografija: str. 33-34. – Abstract V: Disease markers. Section A, Cancer biomarkers. - ISSN 1574-0153.. - Vol. 8, no. 1 (2010/2011), str. 29-34. . - doi: 10.3233/DMA-2011-0817 COBISS.SI-ID 4033599, JCR, WoS, št. citatov do 6. 10. 2011: 0, brez avtocitatov: 0, normirano št. citatov: 0


Predmet: Farmakogenomika

Course title: Pharmacogenomics




Semester Semester



Bioinformatics 2 3

Vrsta predmeta / Course type Izbirni predmet/ Optional subject


Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial




ECTS

15 30 105 6


Jeziki / Languages:




Prerequisits:



Vsebina:


Predstavljene bodo možnosti uporabe najsodobnejših orodij farmakogenomskih raziskav v Sloveniji in svetu, vključno z visoko pretočnimi tehnologijami genske tipizacije, uporabo mikromrež (biočipov) za določanje globalnega profila izražanja genov in uporabo masne spektroskopije v proteomiki. Kandidat bo podrobno seznanjen z različnimi tipi farmakogenomsko molekularnih bioloških označevalcev, kot so polimorfizmi enega nukleotida (SNP), aleli, haplotipi, gensko ekspresijski profili, proteinski profili ter njihovo vlogo v procesu odkrivanja in razvoja novih zdravil kot tudi uporabi že odobrenih zdravil v terapiji. Razložene bodo glavne zakonitosti statistične in populacijske genetike. Prikazani bodo glavni molekularni mehanizmi in geni vključeni v

The students will be provided with information about the state of art technology and bioinformatic tools in pharmacogenomic research including high-throughput genotyping, microarrays and mass spectroscopy. The pharmacogenomic markers such as single nucleotide polymorphisms (SNPs), alleles, haplotypes, gene expression profiles and proteomes and their role in drug discovery and therapy will be discussed. Basics of statistical genetics relevant for pharmaogenomics will be explained. Molecular mechanisms and genes involved in drug metabolism (Cyp450), drug transport (ABCB1/MDR1) and drug receptors will be described. Already known associations between genes and drug response will be comprehensively reviewed. Ethic and social economic issues in pharmacogenomic research and application will be discussed.

metabolizem zdravil (Cyp450), transport zdravil (ABCB1/MDR1) in vezavo zdravil na receptrje. Pregledno bodo prikazani konkretni primeri kliničnih študij znanih korelacij genetske raznolikosti z odzivom na zdravila pri različnih boleznih. Diskutirani bodo etični in socialno ekonomski vidiki farmakogenomskih študij in aplikacij.


1. Kalow W. (ed.): Pharmacogenomics, Marcel Dekker; 1st edition 2001 2. Liciano J. (ed.): Pharmacogenomics, The Search for Individualized Therapies, John Wiley&Sons,

2002R.J.M. 3. Potočnik U, Ferkolj I, Glavač D, Dean M: Polymorphisms in multidrug resistance 1 (MDR1) gene are

associated with refractory Crohn disease and ulcerative colitis. Genes Immun. 2004 Nov;5(7):530-9.



Cilj predmeta je omogočiti študentu razumevanje molekularno genetskih in biokemijskih osnov, ki pogojujejo raznolik odziv na zdravila glede na posameznikovo genetsko predispozicijo, kar bo omogočilo študentu sodelovanje pri izvajanju individualiziranega zdravljenje v praksi kot tudi vodenje lastne študije iskanja novih povezav med gensko predispozicijo in odzivom na zdravljenje ter preverjanje že znanih povezav na različnih populacijah.

The aim of this course is to provide student with understanding of molecular genetic and biochemical mechanisms underlaying different response to drug terapy. Student will be able to collaborate with medical doctors doing presonalized medicine and will be able to design and conduct research for discovery of molecular markers in pharmacogenomic.



Znanje in razumevanje: Študentje bodo razumeli molekularno genetske in biokemijske mehanizme, ki pogojujejo raznolik odziv na zdravila


students will understant molecular genetic and biochemical mechanisms underlying variation in drug response among different individuals



Predavanja

Seminarske vaje

Lectures

Tutorial



Assessment:


pisni in

ustni izpit 60 40


writen and

oral exemination




Predmet: Humana molekularna genetika-izbrana poglavja

Course title: Human moleclar genetics-selcted topics




Semester Semester



Bioinformatics 2 3



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial




ECTS

15 15 15 105 6

Nosilec predmeta / Lecturer: Prof. dr. Damjan Glavač

Jeziki / Languages:




Prerequisits:


Basic knowledge of molecular biology, biochemistry, human genetics and bioinformatics

Vsebina:


Napredna funkcijska genomika Nove metode zdravljenja: genska terapija, uporaba izvornih matičnih celic in terapevtskega kloniranja za transplantacijsko medicino Molekularna genetika raka: onkogeni, tumorsko zaviralni geni, dedne oblike, molekulska diagnostika in zdravljenje, presejalni testi Molekularna genetika in staranje-ali lahko preprečimo staranje? Molekularna evolucija genomov-kaj nas dela ljudi? Genetika vedenja in nevrobiologija

Advances in functional genomics New approaches to treating disease: Gene therapy, embryonic stem cell research and therapeutic cloning for tissue repair and regeneration Molecular cancer genetics: oncogenes, tumors suppressor genes, hereditary cancer, molecular diagnostic and treatment, screening Molecular genetics and aging-can we reverse aging? Molecular evolution of genomes-what make us human? Behavioral genetics and neurobiology


4. STRACHAN T and READ AP: Human Molecular genetics, Gerland Publish, Inc., New York, 3rd ed., 2004 5. Tekoča periodika



Predmet bo seznanil študente z najaktualnejšimi temami na področju humane molekularne genetike. Poseben poudarek bo na poglobljenem razumevanju načinov dedovanja, strukture in primerjave genov in genomov, genetske raznolikosti in genetskih napak povezanih z nastankom bolezni. Študentom bodo predstavljene možnosti, prednosti, omejitve, tveganja in etični vidiki uporabe tehnologij molekularne genetike in genomike v medicinske namene. Poudarek bo tudi na interpretaciji genetskih testov in genetskem svetovanju pri monogenskih in kompleksnih boleznih

The aim of this course is to inform students about most important and atractive up to date topics in the field of human molecular genetics. Students will get deep inside into heredity, structures of genes and genomes, comparative genomics, genomic diversity and mutations associated with diseases. The possibilities, advantages, risk, limitations and ethical issues of molecular genetic and genomic based medicine will be discussed. The interpretation of genetic tests and genetic counseling in rare monogenic and common complex multifactorial diseases will be discussed.




povezave genotipa in kompleksnih fenotipov, zakonitosti dedovanja kompleksnih fenotipov

uporaba molekularne genetike v medicini

branje in razumevanje tekoče znanstvene literature in argumentirano razpravljanje o razvoju znanstvenega področja


corellations genotype-complex phenotype; heredity of complex phenotypes

aplication of molecular genetics in medicine

reading current scientific literature and discussing future developments in the field



Predavanja

Seminarske vaje

Lectures

Tutorial



Assessment:


pisni in

ustni izpit 60 40


writen and

oral exemination


ASSESSMENT of the tumourigenic and metastatic properties of SK-MEL28 melanoma cells surviving electrochemotherapy with bleomycin = Določitev tumorigenih in metastatskih lastnosti melanomskih celic SK-MEL28 po preživetju elektrokemoterapije z bleomicinom / Vesna Todorović ... [et al.]. - . - Dostopno tudi na: http://versita.metapress.com/content/24337t420311w012/fulltext.pdf. - Soavtorji: Gregor Serša, Vid Mlakar, Damjan Glavač, Maja Čemažar. - Izvleček v angl. in slov. - Bibliografija str. 44-45. V: Radiology and oncology. - ISSN 1318-2099.. - Vol. 46, no. 1 (2012), str. 32-45. . - doi: 10.2478/v10019-012-0010-6 COBISS.SI-ID 3203441, JCR, WoS, št. citatov do 11. 4. 2012: 0, brez

avtocitatov: 0, normirano št. citatov: 0 2.MICRORNAS, innate immunity and ventricular rupture in human myocardial infarction / Nina Zidar ... [et al.]. - Soavtorji: Emanuela Boštjančič, Damjan Glavač, Dušan Štajer. - Abstract. - Bibliografija na koncu prispevka. V: Disease markers. - ISSN 0278-0240.. - Vol. 31, issue 5 (2011), str. 259-265 . - doi: 10.3233/DMA-2011-0827 COBISS.SI-ID 29193689, JCR, WoS, št. citatov do 11. 4. 2012: 0, brez avtocitatov: 0, normirano št. citatov: 0 DOWN-regulation of microRNAs of the miR-200 family and miR-205, and an altered expression of classic and desmosomal cadherins in spindle cell carcinoma of the head and neck-hallmark of epithelial-mesenchymal transition / Nina Zidar ... [et al.]. - Ilustr. - Soavtorji: Emanuela Boštjančič, Nina Gale, Nika Kojc, Mario Poljak, Damjan Glavač, Antonio Cardesa. - Summary. - Bibliografija na koncu prispevka. V: Human pathology. - ISSN 0046-8177.. - Vol. 42, issue 4 (2011), str. 482-488. . - doi: 10.1016/j.humpath.2010.07.020 COBISS.SI-ID 28112089, JCR, WoS, št. citatov do 6. 2. 2012: 1, brez avtocitatov: 1, normirano št. citatov: 0


Predmet: MAGISTRSKA NALOGA

Course title: Master Thesis




Semester Semester



Bioinformatics 2 2

Vrsta predmeta / Course type


Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial




ECTS

375 15

Nosilec predmeta / Lecturer: Izbrani mentor/ Mentor selected

Jeziki / Languages:




Prerequisits:

Študent lahko prijavi magistrsko nalogo na osnovi predpisanih pogojev v pravilniku.

The student can apply for the degree’s work according to the prescribed conditions in the regulations.

Vsebina:


Prijava teme magistrske naloge v skladu s Statutom UM in pravilniki FZV UM.

The official procedure of the preparation of the Master Thesis accordingly Statute of University of Maribor and regulations of FHS UM.


Relevantna literatura s področja magistrske naloge. / Relevant literature from the topic of the Master Thesis.



Cilji so definirani v prijavi teme magistrske naloge. The objectives are defined in the application for the approval of the topic of the Master Thesis.



Znanje in razumevanje: Znanje širšega strokovnega področja, v katerega sodi magistrska naloga in ožje znanje ter razumevanje pojmovnika, ki ga zajema tema magistrske naloge. Poudarek je na praktičnih znanjih in naprednejših metodologijah zajemanja, obdelovanja in prikazovanja podatkov.

Knowledge and Understanding: Knowledge of the broader professional field to which belongs the Master Thesis and special knowledge of the corresponding glossary. The emphasis is on the practical skills and relatively more advanced methodologies of collecting, processing and presenting data.

Prenesljive/ključne spretnosti in drugi atributi: Strokovno zapisovanje in izražanje vsebine, obvladanje reševanja strokovnih problemov, suverena predstavitev ključnih spoznanj in spretnost argumentiranja.

Transferable/Key Skills and other attributes: Documenting and expressing the subject in a professional way, mastering the solving of the professional problems, independent presentation of the key conclusions and ability in arguing.



Vodeno individualno raziskovalno delo.

Guided individual research work.



Assessment:

Magistrska naloga Zagovor

70% 30%

Master Thesis Presentation


Predmet: Matematično modeliranje in simulacije v zdravstvu

Course title: Mathematical Modeling and Simulations in Health Science




Semester Semester



Bioinformatics 2 3



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial


work



ECTS

15 30 105 6


Jeziki / Languages:

Predavanja / Lectures: slovenski/Slovenian

Vaje / Tutorial: slovenski/Slovenian


Prerequisits:

Ni pogojev. No prerequisites.

Vsebina:


Vsebina predavanj: Predmet zajema obravnavo izbranih primerov matematičnega modeliranja bioloških procesov s stališča zdravstva s poudarkom na primerih s področja:

- cirkulacije krvi - mehanike dihanja - izmenjave plinov v pljučih in v krvi - kontrole celičnega volumna - mehanike mišic - signalizacije v celici in med celicami - bioloških ritmov - biomehanike - populacijske dinamike

Vsebina laboratorijskih vaj:

- matematično modeliranje in računalniška

Lectures outline:

The subject introduces selected examples of

mathematical modeling biological processes from

the health care point of view with emphasis on:

- blood circulation - mechanics of breathing - gas exchange in lungs and blood - control of cell volume - muscle mechanics - intracellular and intercellular signaling - biological rhythms - biomechanics - population dynamics

simulacija izbranih procesov - računalniška simulacija in vizualizacija

rezultatov z računalniškimi orodji

Laboratory work outline:

- mathematical modeling and computer simulation of selected processes

- computer simulation and visualization of results with computer tools


Hoppensteadt F. C., Peskin C. S. Modeling and Simulation in Medicine and the Life Sciences, Springer-Verlag, New York 2004. Keener J., Sneyd J. Mathematical Physiology, Springer-Verlag, New York 1998 Goldbeter A. Biochemical Oscillations and Cellular Rhythms, Cambridge University Press, Cambridge 1996 Hobbie R. K. Intermediate Physics for Medicine and Biology, John Wiley & Sons, New York 1988



Predmet je usmerjen v obravnavo bioloških procesov na ravni človeškega organizma in populacije s stališča modeliranja in simulacij, katerega poglavitni cilj je poglobljen študij izbranih procesov in njihova aplikacija v zdravstvu z metodami matematičnega modeliranja in računalniških simulacij.

The subject is focused on the biological processes on the level of human organism as well as on the level of population from the point of view of modeling and simulation. The major aim is to study selected processes and its application in health science with methods of mathematical modeling and computer simulations.



Znanje in razumevanje: Študent pridobi:

- poznavanje in razumevanje posameznih fizioloških procesov na ravni matematičnega modela;

- znanje o izbranih procesih v smislu poznavanja aktualne problematike, ki omogoča nadaljnje raziskave.

Knowledge and Understanding: Student gets:

- knowledge and understanding of selected physiological processes on the level of mathematical model;

- knowledge of the selected processes studied in details. This enables her/him further research in this field.



Predavanja

Laboratorijske vaje

Lectures

Laboratory work



Assessment:


Ustni izpit

Praktično delo v laboratoriju in domače naloge

50 50


• Oral exam • Practical work in laboratory and

Homework


FAJMUT, Aleš MLC-kinase/phosphatase control of Ca[sup]2+ signal transduction in airway smooth muscles / Aleš Fajmut,

Milan Brumen. - . - Dostopno tudi na: http://dx.doi.org/10.1016/j.jtbi.2007.10.005. - Available online Oct. 11 2007. - Bibliografija: str. 481. V: Journal of theoretical biology. - ISSN 0022-5193.. - Vol. 252, no. 3 (2008), str. 474-481. . - doi: 10.1016/j.jtbi.2007.10.005 COBISS.SI-ID 15856392, JCR, WoS, št. citatov do 6. 5. 2011: 5, brez avtocitatov: 4, normirano št. citatov: 2 CONTRIBUTION of Rho kinase to the early phase of the calcium-contraction coupling in airway smooth muscle / Prisca Mbikou ... [et al.]. - Ilustr. - Nasl. z nasl. zaslona. - Opis vira z dne 7. 12. 2010. - Soavtorji: Ales Fajmut, Milan Brumen, Etienne Roux. - Bibliografija: str. 257-258. - Abstract. V: Experimental physiology. - ISSN 0958-0670.. - Vol. 96, issue 2 (2011), str. 240-258. . - doi: 10.1113/expphysiol.2010.054635 COBISS.SI-ID 18009864, JCR, WoS, št. citatov do 10. 4. 2012: 2, brez avtocitatov: 2, normirano št. citatov: 1 DOBOVIŠEK, Andrej Role of expression of prostaglandin synthases 1 and 2 and leukotriene C [sub] 4 synthase in aspirin-intolerant asthma: a theoretical study / A. Dobovišek, A. Fajmut, M. Brumen. - Bibliografija: str. 277-278. - Abstract.V: Journal of pharmacokinetics and pharmacodynamics. - ISSN 1567-567X.. - Vol. 38, no. 2 (2011), str. 261-278. . - doi: 10.1007/s10928-011-9192-6 COBISS.SI-ID 18203144, JCR, WoS, št. citatov do 6. 4. 2012: 1, brez avtocitatov: 0, normirano št. citatov: 0


Predmet: Napredne raziskovalne metode v bioinformatiki

Course title: Advanced research methodology in bioinformatics




Semester Semester



Bioinformatics 2 4



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial




ECTS

15 30 105 6

Nosilec predmeta / Lecturer: Izr. prof. dr. Gregor Štiglic

Jeziki / Languages:




Prerequisits:

Ni pogojev. None.

Vsebina:


Študent pridobi poglobljena znanja s področja metodologije znanstvenega dela, kvantitativnega in kvalitativnega raziskovanja.

Ta predmet je namenjen pripravi študentov za izvajanje visoko kakovostnih raziskav s področja bioinformatike.

Na primerih s področja bioinformatike bodo študentje nadgradili svoje znanje z naprednimi metodami kvalitativne in kvantitativne analize podatkov ter podatkovnega rudarjenja z uporabo programskega jezika R.

The student gets familiar with methodological issues and process of scientific research especially qualitative and quantitative research. This subject aims to prepare students for the practice of undertaking high quality research methodology, quantitative and qualitative research in bioinformatics. Based on examples from bioinformatics, students will upgrade their knowledge on advanced methods of qualitative and quantitative data analysis using R programing language.


1. Kabacoff, R. (2011). R in Action. Manning Publications Co. (http://www.statmethods.net). 2. Teetor, P. (2011). R cookbook. O'Reilly Media, Inc. (http://www.cookbook-r.com/). 3. Adler, J. (2010). R in a Nutshell, A Desktop Quick Reference, O'Reilly Media, 2010

(http://web.udl.es/Biomath/Bioestadistica/R/Manuals/r_in_a_nutshell.pdf). 4. Garrett, G., Hadley, W. (2016) R for Data Science, O'Reilly (http://garrettgman.github.io/). 5. Hadley W. (2014) Advanced R, Chapman and Hall/CRC (http://adv-r.had.co.nz/).



Študent: - obvlada napredne raziskovalne paradigme

in raziskovalne pristope, ki oblikujejo bioinformatiko in

- spozna pomen in značilnosti raziskovanja in raziskovalnega dela v bioinformatiki;

Ob uspešnem zaključku tega predmeta bodo študenti:

Poznali postopke za načrtovanje kvalitativnega in kvantitativnega raziskovanja s posebnim poudarkom na temah, ki so zanimive za bioinformatiko;

Obvladali uporabo različnih tehnik in metod zbiranja in analiziranja kvalitativnih in kvantitativnih podatkov.

Poznali pristope, ki so nujno potrebni za učinkovito širjenje in vrednotenje kvalitativnega in kvantitativnega raziskovanja.

Student is acquainted with: - research paradigms and research

approaches which form bioinformatics and - recognizes significance and characteristics

of research in bioinformatics; On successful completion of this course students will:

Know the process of qualitative and quantitative research design, with particular emphasis on bioinformatics related topics.

Become skilled in the use of a range of techniques for the collection and analysis of qualitative and quantitative data.

Know how to use approaches essential for the effective dissemination and evaluation of qualitative and quantitative research.




Poznavanje napredne raziskovalne metodologije in raziskovalnih pristopov;

Usposobljenost za samostojno kvalitativno in kvantitativno raziskovanje;

Študent bo sposoben samostojno oblikovati in sporočati svoja opažanja in svoje rezultate ter se vključevati v aktivno objavljanje raziskovalnih prispevkov na področju bioinformatike.


Knowledge of advanced research methodology and different research approaches;

Qualified for independent quantitative and qualitative research;

Student will be able to independently form and report their observations and results and actively comprehend in publishing of research contributions in the field of bioinformatics.



Predavanja, seminarji.

Lectures, seminars.



Assessment:

http://www.statmethods.net/

http://www.cookbook-r.com/

http://web.udl.es/Biomath/Bioestadistica/R/Manuals/r_in_a_nutshell.pdf

http://garrettgman.github.io/

http://adv-r.had.co.nz/

Način (pisni izpit, ustno izpraševanje, naloge, projekt) Projekt

100

Type (examination, oral, coursework, project): Project


Callahan, A., Pernek, I., Stiglic, G., Leskovec, J., Strasberg, H. R., & Shah, N. H. (2015). Analyzing Information Seeking and Drug-Safety Alert Response by Health Care Professionals as New Methods for Surveillance. Journal of medical Internet research, 17(8), e204. Stiglic, G., Wang, F., Davey, A., & Obradovic, Z. (2014). Pediatric Readmission Classification Using Stacked Regularized Logistic Regression Models. In AMIA Annual Symposium Proceedings (Vol. 2014, p. 1072). American Medical Informatics Association. Stiglic, G., Kocbek, S., Pernek, I., & Kokol, P. (2012). Comprehensive decision tree models in bioinformatics. PloS one, 7(3), e33812.


Predmet: Osnove molekularne in populacijske genetike

Course title: Basics of molecular and population genetics




Semester Semester



Bioinformatics 2 3



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial




ECTS

15 30 90 6


Jeziki / Languages:




Prerequisits:

Poznavanje osnov molekularne biologije. Understanding basics of molecular biology

Vsebina:


Osnove molekularne genetike: DNA struktura in lastnosti, replikacija (prokarionti, eukarionti), rekombinacija DNA, DNA popravljalni, mehanizmi, mehanizem nastanka DNA mutacij, organizacija, struktura in funkcija genov, struktura genoma (rastlinski, živalski in človeški), transkripcija, translacija, regulacija genske ekspresije

Osnove dedovanja, kromosomska teorija dednosti, Mendlovo dedovanje, poligensko dedovanje

Gensko mapiranje, mitohondrijski genom

Mutacije, polimorfizmi v DNA in v proteinih, fenotip, genotip, alelna frekvenca, haplotipi, haplotiski bloki (projekt HapMap), Hardy-Weinbergov zakon, analiza genetske vezave, vezavno neravnotežje (linkage disequilibrium)

Basic molecular genetics: DNA structure and characteristics, replication (prokaryotes, eukaryotes), recombination, repair and mutations, organization, structure and function of genes and chromosomes, genome structure (plant, animal, human) transcription (prokaryotes, eukaryotes), translation, regulation of gene expression

Chromosomal basis of heredity, Mendelian inheritance, polygenic inheritance

Gene mapping, mitochondrial genome

Mutations, polymorphisms, phenotype, genotype, allele frequency, haplotypes, haplotype blocks (HapMap project), the Hardy-Weinberg law, linkage analysis, linkage disequilibrium.

Size and structure of population

Natural selection, mutations, genetic drift, gene flow, inbreeding

Velikost in struktura populacije

Naravni izbor, mutacije, genetski zdrs, genski pretok, parjenje v sorodstvu

Molekularna evolucija, molekularna ura, nastanek genomov, genetika ogroženih vrst

Kvantitativna genetika

Genetsko testiranje posameznikov in populacije: metode genske tipizacije in določanja mutacij, genski testi v medicini (monogenske genetske bolezni, kompleksne genetske bolezni), preiskava DNA za tipizacijo tkiv in za osebno identifikacijo (forenzika)

Vloga molekularne in populacijske genetike v sodobni družbi: etični, sociološki in ekonomski vidiki

Molecular evolution, molecular clocks, how genomes evolve, conservation genetics

Quantitative traits

Gene testing in individuals and populations: mutation detection and genotyping methods, genetic testing in medicine (genetic diseases with classical Mendelian and complex inheritance), DNA analysis in forensics and bone marrow transplantation typing

Molecular and population genetic and society: ethical, social and economical issues


HEDRICK PW: Genetics of Populations, Jones & Bartlett Publishers, Sudbury, Inc., 3rd ed, 2004

STRACHAN T and READ AP: Human Molecular genetics, Gerland Publish, Inc., New York, 3rd ed., 2004

KLUG M and CUMMINGS MR.: Genetics: A Molecular Perspective. Pearson Education, Inc. New Jersey, 2003



Študenti bodo seznanjeni z osnovnimi koncepti populacijske genetike. Povdarek v razumevanju genetske raznolikosti populacije in evolucijsko pomebnih genov bo na interpretaciji novih informacij pridobljenih z modernimi pristopi molekularne genetike kot so sekvenciranje celotnih genomov in primerjalna genomika.

Students will be provided with basic population genetics principles. The focus will be on new molecular data including genome projects that compare population samples to identify patterns of genetic diversity and genes that have been under selection which helps to understand molecular evolution.




zakonitosti prenosa genetske informacije med generacijami

povezave med genotipom in fenotipom

dejavniki, ki vplivajo na frekvenco DNA polimorfizmov in genetsko raznolikost v različnih populacijah vloga mutacij in genetske raznolikosti v molekularni evouluciji


principals of heredity and transfer of genetic information between generations

correlations genotype-phenotype

factors that influence frequency of DNA polymorphisms and genetic diversity in different populations the role of mutations and genetic diversity in evolution



Predavanja

Seminarske vaje

Lectures

Tutorial



Assessment:


pisni in

ustni izpit 60 40


writen and

oral exemination




Predmet: Proteinske strukture in proteomika

Course title: Proteine structures and proteomics




Semester Semester



Bioinformatics 2 3



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial




ECTS

15 30 30 6

Nosilec predmeta / Lecturer: Prof. dr. Damjan Glavač

Jeziki / Languages:




Prerequisits:

Poznavanje osnov molekularne biologije, biokemije, molekularne genetike in bioinformatike

Understanding basics of molecular biology, biochemistry, molecular genetics and bioinformatics

Vsebina:


Osnove proteomike: osnovne definicije, izolacija proteinov, kromatografske metode, identifikacija in karakterizacija proteinov, elektroforeza, analiza gelov, masna spektrometrija, analiza sekvence proteinov, proteomske baze podatkov

Osnove proteinske strukture: lastnosti aminokislin, peptidna vez, osnovni elementi proteinskih struktur, sile med molekulami, geometrija proteinov

Sekundarne strukture proteinov in njihovi motivi, primeri alfa, beta in alfa-beta struktur

Osnove zvijanja proteinov

Struktura proteinov določa njihovo funkcijo: proteini ki se vežejo na DNK, primeri encimske katalize, membranski proteini, prenos signalov, fibrilarni proteini, strukture molekul, ki sodelujejo pri imunskem odzivu, strukture virusov

Interakcijska proteomika, proteinski kompleksi

Določanje strukture proteinov: rentgenska kristalografija, NMR, elektronska mikroskopija, kristalizacija proteinov

Strukturna genomika: osnovni principi in metode

Načrtovanje zdravil na osnovi struktur proteinov, iskanje primernih tarčnih proteinov in silico, modeliranje proteinov

Baza podatkov tridimenzionalnih struktur proteinov in uporaba le-te

Proteomics basics: definitions, separation of proteins, chromatographic methods, protein identification and characterization, elecrophoresis, image analysis, mass spectrometry, protein sequence analysis, proteomics databases

Basics of protein structure: properties of, amino acids, peptide bond, building blocks of protein structures, overview of molecular forces, protein geometry

Secondary structures, motifs of protein structure, alpha, beta and alpha-beta motifs in protein structures

Basics of protein folding

Structure- function relationship: DNA binding proteins, examples of enzyme catalysis, membrane proteins, signal transduction, fibrous proteins, structures of the immune response molecules, virus structures

Interaction proteomics, protein complexes

Protein structure determination: X-ray crystallography, protein crystallization, NMR, electron microscopy

Structural genomics: basic principles and methods

Structural based drug design, in silico screening, protein modelling

Protein data bank (PDB) and its use


1. Carl-Ivar Branden and John Tooze. Introduction to Protein Structure, 2nd edition, 1999, Garland Publishing

2. Donald Voet & Judith Voet, Biochemistry, J.Wiley&Sons, 2004, 3rd ed. 3. Gale Rhodes, Crystallography Made Crystal Clear- A Guide for Users of Macromolecular Models, Third

Edition, February 2006, Elsevier/Academic Press 4. Twyman, R. M. 2004. Principles of proteomics. BIOS Scientific Publishers, New York. 5. Liebler, D. C. 2002. Introduction to proteomics: tools for the new biology. Humana Press, Totowa, NJ. 6. Mechanisms of Protein Folding, 2nd edn., (2000) R.H. Pain (ed.), Oxford University Press 7. A. Skoog, F. J. Holler and T. A. Nieman, Principles of Instrumental Analysis, 5th Edition, Saunders College

Publishing, Philadelphia, 1998.



Cilj predmeta je študente sezaniti z osnovnimi principi struktur proteinov, proteomike in metodami, ki se pri tem uporabljajo.

The overall course objective is to provide the student with a broad understanding of the main fundamentals of the protein structure, proteomics and methods that are used in that field.



Znanje in razumevanje: Po uspešnem zaključku naj bi bil študent/ka sposoben:

Opisati osnovne principe strukture proteinov, proteinske motive, lastnosti sekundarne strukture in zvijanja proteinov.

Pojasniti zvezo med strukturo in funkcijo proteinov

Opisati metode, ki se uporabljajo pri karakterizaciji proteinov in določanju njihove strukture ter razložiti kako se to lahko uporabi v industriji

Uporabljati računalniške programe za prikaz, primerjavo in analizo proteinskih struktur in te strukture tudi interpretirati.

Knowledge and understanding: On successful completion of this course, student should be able to:

Describe basic principles of protein structure, protein structure motifs, secondary structure properties and protein folding.

Explain structure function relationship. Describe methodologies used for protein

characterization and structure determination and how these techniques can be applied to industry objectives and outcomes

Use computer sotware to visualise, compare, analyse and interpret protein structures



Predavanja

Seminarske vaje

Seminar

Lectures

Tutorials

Seminar



Assessment:


pisni in ustni izpit

seminar

70 30


writen and oral exemination

seminar


ASSESSMENT of the tumourigenic and metastatic properties of SK-MEL28 melanoma cells surviving electrochemotherapy with bleomycin = Določitev tumorigenih in metastatskih lastnosti melanomskih celic SK-MEL28 po preživetju elektrokemoterapije z bleomicinom / Vesna Todorović ... [et al.]. - . - Dostopno tudi na: http://versita.metapress.com/content/24337t420311w012/fulltext.pdf. - Soavtorji: Gregor Serša, Vid Mlakar, Damjan Glavač, Maja Čemažar. - Izvleček v angl. in slov. - Bibliografija str. 44-45. V: Radiology and oncology. - ISSN 1318-2099.. - Vol. 46, no. 1 (2012), str. 32-45. . - doi: 10.2478/v10019-012-0010-6 COBISS.SI-ID 3203441, JCR, WoS, št. citatov do 11. 4. 2012: 0, brez avtocitatov: 0, normirano št. citatov: 0 2.MICRORNAS, innate immunity and ventricular rupture in human myocardial infarction / Nina Zidar ... [et al.]. - Soavtorji: Emanuela Boštjančič, Damjan Glavač, Dušan Štajer. - Abstract. - Bibliografija na koncu prispevka. V: Disease markers. - ISSN 0278-0240.. - Vol. 31, issue 5 (2011), str. 259-265 . - doi: 10.3233/DMA-2011-0827 COBISS.SI-ID 29193689, JCR, WoS, št. citatov do 11. 4. 2012: 0, brez avtocitatov: 0, normirano št. citatov: 0 DOWN-regulation of microRNAs of the miR-200 family and miR-205, and an altered expression of classic and desmosomal cadherins in spindle cell carcinoma of the head and neck-hallmark of epithelial-mesenchymal transition / Nina Zidar ... [et al.]. - Ilustr. - Soavtorji: Emanuela Boštjančič, Nina Gale, Nika Kojc, Mario Poljak, Damjan Glavač, Antonio Cardesa. - Summary. - Bibliografija na koncu prispevka. V: Human pathology. - ISSN 0046-8177.. - Vol. 42, issue 4 (2011), str. 482-488. . - doi: 10.1016/j.humpath.2010.07.020 COBISS.SI-ID 28112089, JCR, WoS, št. citatov do 6. 2. 2012: 1, brez avtocitatov: 1, normirano št. citatov: 0


Predmet: Rekombinantna DNA tehnologija

Course title: Recombinant DNA technology




Semester Semester



Bioinformatics 2 3



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial




ECTS

15 30 105 6


Jeziki / Languages:




Prerequisits:

Poznavanje osnov molekularne biologije in molekularne genetike

Understanding basics of molecular biology and molecular genetics

Vsebina:


Kloniranje: Gostiteljski organizmi, vektorji, strategije kloniranja v prokariontske in evkariontske orgnizme, transformacija in transfekcija, ekspresija rekombinantnih proteinov

Priprava genomskih in cDNA knjižnic

Hibridizacije nukleinskih kislin, mikromreže

Pomnoževanje molekul DNA v pogojih in vitro (PCR), Sekvenciranje DNA

Dvohibridni kvasni sistem za določanje interakcij protein-protein

Spreminjanje genov - in vitro mutageneza, živalski modeli z izbitim genom-pomen v funkcijski genomiki in bolezenskih modelih

Preprečevanje izražanja genov - protismiselna tehnologija, siRNA

Kloniranje človeških genov, reproduktivno kloniranje sesalcev, terapeutsko kloniranje

Cloning: Host organisms, DNA cloning vectors, cloning strategy in eukaryotes and prokaryotes, transformation and transfect ion, expression of recombinant proteins

preparation of genomic and cDNA libraries

Hybridization of nucleic acids, DNA micro arrays

Polymerase DNA reaction (PCR), DNA sequencing

Yeast two-hybrid system for identification of protein-protein interaction

Site directed mutagenesis, knock-out technology and animal models-the role in functional genomics and animal disease models

Silencing gene expression: RNAi, antisense RNA technology

Cloning human genes, reproductive cloning

Transgene rastline in živali

Preiskava DNA za tipizacijo tkiv in za osebno identifikacijo

Genska tehnologija pri proizvodnji zdravil in diagnostičnih sredstev

Zakonodaja in varnostni predpisi za delo z genetsko spremenjenimi organizmi

Vloga rekombinantne DNA tehnologije v sodobni družba: etični, sociološki in ekonomski vidiki

of mammalians, therapeutic cloning

Transgenic plants and animals

DNA fingerprinting in forensics

Gene technology in drug production and diagnostics

Low regulations and safety precautions for research and applications of genetic modified organisms

Recombinant DNA technology and society: ethic and social economic issues


8. Bernard R. Glick, Jack J. Pasternak: Principles and applications of recombinant DNA, 3rd edition, ASM Press, Washington, 2003

9. Sandy Primrose, Richard Twyman, Bob Old: Principles of Gene Manipulation, 6th edition, Blackwell Science, Oxford, 2001



Študenti bodo spoznali osnovne tehnike in uporabo rekombinantne DNA tehnologije v raziskavah in v praksi.

Students will be provided with basic techniques and applications of recombinant DNA technology in research and industry.




tehnike in principi kloniranja DNA in ostalih pristopov v rekombinanti DNA tehnologiji

uporaba rekombinantne DNA tehnologije v raziskavah in praksi


techiques and principals of DNA cloning and other recombinant DNA technology

applications of recombinant DNA technology in research and industry



Predavanja

Seminarske vaje

Lectures

Tutorial



Assessment:


pisni in

ustni izpit 60 40


writen and

oral exemination




Predmet: Seminar

Course title: Seminar




Semester Semester



Bioinformatics 2 2

Vrsta predmeta / Course type


Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial




ECTS

30 195 9

Nosilec predmeta / Lecturer: Visokošolski učitelji na študijskem programu

Jeziki / Languages:




Prerequisits:

Ni pogojev. No prerequisites.

Vsebina:


Glede na izbrane izbirne predmete ter magistrsko temo bo določena tudi vsebina seminarja, ki bo zajemala predvsem individualno raziskovalno delo. Individualno raziskovalno delo bo študent opisal v poročilu. Poročilo zajema 20-25 strani in bo oblikovano podobno kot magistrska naloga.

Dependent on selected subjects and the theme of master work the content will be defined. The content will consist mainly on the individual research work. Student will present the individual research work in the report, structured in the same manner as master thesis (20-25 pages).


Relevantna literatura s področja seminarske naloge. / Relevant literature from the topic of the coursework.



Pripraviti študenta za individualno raziskovalno delo in uporabo teoretskih konceptov v praksi. V seminarski nalogi študent pokaže sposobnost izbire in uporabe domače ter tuje strokovne literature in dodatnih virov za potrebe rešitve izbranega problema. Strokovno zapisovanje in izražanje vsebine, obvladanje reševanja strokovnih problemov, predstavitev ključnih spoznanj in spretnost argumentiranja.

Prepare student on individual research work and to apply theoretical backgrounds in practical work. In coursework the student presents the ability to choose and use his national and foreign professional literature and additional sources in order to solve the chosen problem. Documenting and expressing the subject in a professional way, mastering the solving of the professional problems, independent presentation of the conclusions and ability in arguing.



Znanje in razumevanje: Znanje širšega strokovnega področja, v katerega sodi seminarska naloga in ožje znanje ter razumevanje pojmovnika, ki ga zajema tema. Poudarek je na praktičnih znanjih in enostavnejših metodologijah zajemanja, obdelovanja in prikazovanja podatkov.

Knowledge and understanding: Knowledge of the broader professional field to which belongs the coursework and special knowledge of the corresponding glossary. The emphasis is on the practical skills and relatively more simple methodologies of collecting, processing and presenting data.



Mentor na konzultacijah preverja vsebinski in strukturni vidik naloge.

The content and the structural aspect of the coursework is monitored by tutor during his consultations.



Assessment:

Način (pisni izpit, ustno izpraševanje, naloge, projekt) Ustna predstavitev seminarske naloge Pisni izdelek seminarske naloge

30 % 70 %

Type (examination, oral, coursework, project): Oral presentation of coursework. Written presentation of coursework.


Predmet: Teoretična biofizika

Course title: Theoretical Biophysics




Semester Semester



Bioinformatics 2 3



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial


work



ECTS

30 15 15 90 6


Jeziki / Languages:




Prerequisits:

Potrebno je formalno ali neformalno znanje pridobljeno pri predmetu Osnove biofizike in Molekularna biofizika.

Formal or informal knowledge of subjects Introduction to Biophysics and Molecular Biophysics is required.

Vsebina:


Splošni opis predmeta: Vsebina predmeta bo temeljila na aplikaciji najnovejših teoretičnih (fizikalnih, kemijskih, matematičnih in računalniških) metod in orodij na biološko orientirane probleme in situacije. Obravnavano bo delovanje različnih kompleksnih bioloških sistemov, kot so metabolični sistemi, signalne mreže, organele, celice, organi, organizmi in populacije z vidika študija in obravnave delovanja njegovih sestavnih delov. Na podlagi razumevanja odnosov in interakcij med pod enotami kompleksnejšega sistema bo na ta način mogoče sklepati tudi na delovanje sistema kot celote. Vsebina predavanj:

- UVOD: (fizikalni in matematični principi,

General description of the subject: The subject introduces theoretical and computational tools and cutting edge research approaches from physics, chemistry, mathematics and computer science in the context of biological problems and situations. Functioning of different complex biological systems such as metabolic system, signaling networks, organelles, cells, organs, organisms and populations will be discussed from the point of view of studying their integral parts. On the basis of understanding the interactions and relationships between the systems subunits it will be possible to deduce to the functioning of the system as integrity. Lectures outline:

- INTRODUCTION: (principles from physics

delo z računalniškimi orodji za matematično modeliranje in delo z bazami podatkov)

- STANDARDNI PRISTOPI K MODELIRANJU BIOLOŠKIH SISTEMOV: (biokemijska in encimska kinetika, metabolične mreže, kontrolna analiza, signalne mreže)

- IZBRANI PRIMERI MODELIRANJA BIOLOŠKIH SISTEMOV: (oscilacije v bioloških sistemih, prenos signalov, krčenje mišic, modeliranje delovanja celic, celostno modeliranje celice, celični cikel, staranje, ekspresija genov, evolucija in samoorganizacija)

Vsebina seminarja: Študent izbere eno izmed tem, ki jih razpiše predavatelj. Projektna naloga ima obliko krajšega znanstvenega prispevka. Študent po izdelavi in predavateljevem pregledu naloge pripravi predstavitev pred kolegi. Vsebina laboratorijskih vaj:

- spoznavanje z računalniškimi orodji, kot so npr. Mathematica, MatLab, Madonna, Gepasi, PLAS, Model Maker, Virtual Cell…

- delo z računalniškimi podatkovnimi bazami in orodji na svetovnem spletu kot so npr. BRENDA, Swiss-Prot, TrEMBL, UniProt…

- modeliranje izbranih bioloških sistemov - reševanje matematičnih modelov in

vizualizacija rezultatov s pomočjo računalniških orodij

and mathematics in systems biology, principles of working with computer tools for mathematical modeling and working with databases)

- STANDARD APPROACHES IN MODELING BIOLOGICAL SYSTEMS: (biochemical and enzyme kinetics, metabolic networks, control analysis, signal transduction pathways)

- SELECTED EXAMPLES OF MODELING BIOLOGICAL SYSTEMS: (oscillations in biological systems, signal transduction, muscle contraction, whole cell modeling, cell cycle, aging, gene expression, evolution and self-organization)

Seminar outline: Student chooses one of the themes offered by the lecturer. Project has a form of short scientific contribution. After the review of the final version student presents his project for the colleagues. Laboratory work outline:

- work with computer tools like Mathematica, MatLab, Madonna, Gepasi, PLAS, Model Maker, Virtual Cell…

- work with computer databases from the internet like BRENDA, Swiss-Prot, TrEMBL, UniProt…

- modeling of selected problems from systems biology

- solving of mathematical models and visualization of the results with help of computer tools


1. Klipp E., Herwig R., Kowald A., Wierling C., Lehrach H. Systems Biology in Practice, Wiley-VCH, Weinheim 2005

2. Kitano H. Foundations of Systems Biology, MIT Press, Cambridge 2001 3. Voit E.O. Computational Analysis of Biochemical Systems: A Practical Guide for Biochemists

and Molecular Biologists, Cambridge University Press, New York 2000 4. Vodovnik L., Miklavčič D., Kotnik T. Biološki sistemi, Univerza v Ljubljani, Fakulteta za

elektrotehniko, Ljubljana 1998



- Pri študentih razviti razumevanje kako in zakaj je teoretični pristop k obravnavi bioloških sistemov koristen za razvoj novih eksperimentov

- Študentom prikazati kako lahko dajo teoretični rezultati nov vpogled v delovanje

- To develop an understanding of how and why theoretical approaches can drive new experiments.

- To show students how theoretical results can deliver novel insight into the functioning of biosystems.

bioloških sistemov - Študente seznaniti z aktualnimi

raziskovalnimi teoretičnimi metodami s področja bio-znanosti

Študent spozna, da se da z matematičnim modeliranjem preizkušati hipoteze, ki izhajajo s področja molekularne biologije, fiziologije ali biokemije. Študentje bodo zapustili predmet z zmožnostjo boljšega identificiranja pomembnih nerešenih problemov v bio-znanostih in z zmožnostjo ocenitve kako izbrati in rešiti probleme pri katerih je teoretični in kvantitativni pristop smiseln in produktiven.

- To get an insight into the current theoretical research approaches in bio-sciences.

To get an insight how to test the hypotheses resulting from molecular biology, physiology or biochemistry with mathematical modeling. Students should leave the subject better able to identify important unsolved problems in biology and with an appreciation of how to select and solve problems for which quantitative and theoretical approaches will be productive.



Znanje in razumevanje: Študent pridobi:

- poznavanje in razumevanje fizikalnih, kemijskih, matematičnih in računalniških metod, ki se uporabljajo pri teoretičnem študiju bioloških sistemov;

- zmožnost dela s predstavljenimi računalniškimi orodji in poznavanje drugih;

- razumevanje obravnavanih teoretičnih primerov, poznavanje njihovih prednosti in slabosti ter seznanjenost z drugimi podobnimi primeri.


Student gets: - knowledge and understanding of physical,

chemical, mathematical and computational methods in theoretical approach to study biological systems;

- ability of working with presented computational tools and having acquaintance with others;

- understanding of presented theoretical examples, knowledge of their advantages and disadvantages, as well as having acquaintance with other similar examples.



Predavanja

Seminar

Laboratorijske vaje

Lectures

Seminar

Laboratory work



Assessment:


Ustno in pisno

Praktično delo v laboratoriju in domače naloge

Seminarska naloga

40 30 30


Oral

Written

Project


FAJMUT, Aleš MLC-kinase/phosphatase control of Ca[sup]2+ signal transduction in airway smooth muscles / Aleš Fajmut, Milan Brumen. - . - Dostopno tudi na: http://dx.doi.org/10.1016/j.jtbi.2007.10.005. - Available online Oct. 11 2007. - Bibliografija: str. 481. V: Journal of theoretical biology. - ISSN 0022-5193.. - Vol. 252, no. 3 (2008), str. 474-481. . - doi: 10.1016/j.jtbi.2007.10.005 COBISS.SI-ID 15856392, JCR, WoS, št. citatov do 6. 5. 2011: 5, brez avtocitatov: 4, normirano št. citatov: 2 CONTRIBUTION of Rho kinase to the early phase of the calcium-contraction coupling in airway smooth muscle / Prisca Mbikou ... [et al.]. - Ilustr. - Nasl. z nasl. zaslona. - Opis vira z dne 7. 12. 2010. - Soavtorji: Ales Fajmut, Milan Brumen, Etienne Roux. - Bibliografija: str. 257-258. - Abstract. V: Experimental physiology. - ISSN 0958-0670.. - Vol. 96, issue 2 (2011), str. 240-258. . - doi: 10.1113/expphysiol.2010.054635 COBISS.SI-ID 18009864, JCR, WoS, št. citatov do 10. 4. 2012: 2, brez avtocitatov: 2, normirano št. citatov: 1 DOBOVIŠEK, Andrej Role of expression of prostaglandin synthases 1 and 2 and leukotriene C [sub] 4 synthase in aspirin-intolerant asthma: a theoretical study / A. Dobovišek, A. Fajmut, M. Brumen. - Bibliografija: str. 277-278. - Abstract.V: Journal of pharmacokinetics and pharmacodynamics. - ISSN 1567-567X.. - Vol. 38, no. 2 (2011), str. 261-278. . - doi: 10.1007/s10928-011-9192-6 COBISS.SI-ID 18203144, JCR, WoS, št. citatov do 6. 4. 2012: 1, brez avtocitatov: 0, normirano št. citatov:


Predmet: Teorija kompleksnosti s kaosom

Course title: Complexity theory and chaos




Semester Semester



Bioinformatics 2 3



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial




ECTS

15 30 105 6

Nosilec predmeta / Lecturer: Prof. dr. Peter Kokol

Jeziki / Languages:




Prerequisits:

Ni pogojev.

None.

Vsebina:


Zgodovina

Koncepti teorije sistemov

Definicija kompleksnosti.

Teorija kompleksnosti.

Teorija kaosa

Kompleksni sistemi in teorija kaosa uporabni v računalništvu.

Kompleksni sistemi in teorija kaosa uporabni v biologiji

Kompleksni sistemi in teorija kaosa uporabni v ekonomiji

Aplikacije kompleksnih sistemov in teorije kaosa v bionformatiki

Mehka teorija sistemov.

Uporaba mehke teorije sistemov pri odločanju, reševanju konfliktnih položajev in načrtovanju.

History

The concepts of system theory

Definition of complexity

Theory of complexity

Theory of chaos

Complex systems and chaos theory in computer science

Complex systems and chaos theory in biology

Complex systems and chaos theory in economy

Application of complex systems and chaos theory in bionformatics

Soft system theory

Soft system theory and decision making, problem solving in conflicts situations and planning


1. P. Checkland: Systems Thinking Practice, John Wiley & Sons, Chichester, 1981. 2. P. Checkland, J. Scholes: Soft Systems Methodology in Action, John Wiley & Sons, Chichester, 1990. 3. R. L. Flood, M. C. Jackson: Creative problem Solving: Total System Intervention, John Wiley & Sons,

1991. 4. R. Peitgen: Chaos and Fractals – New Frontiers of Science, Springer Verlag, 1993 5. K. Frenken: Innovation, Evolution and Complexity Theory, EE Press, 2006)



Prvi cilj predmeta je naučiti študente, kakšna je razlika med znanstvenim in sistemskim pristopom in nato metodologije in koncepte sistemskega pristopa, teorija kompleksnosti in teorije kaosa. Drugi, bolj pragmatičen cilj je naučiti študente uporabe zgornjih teorij pri praktičnih primerih iz bioinformatike. Študentje morajo dojeti Aristotelov izrek, ki pravi, da je celota več, kot le vsota njenih posameznih delov.

The first goal is to teach students to understand the differences between scientific approach and system theory and the concepts of system theory, complexity theory and the chaos theory. The other more pragmatic goal is to teach the students how to use the above theories in bioinformatics. The students should be able to understand the Aristotle’s rule that the whole is more then the sum of its parts.



Znanje in razumevanje: Študent:

Razume razliko med znanstvenim in sistemskim pristopom

Študent razume Aristotelov izrek

Sistem pridobi kompetence iz teorije

Knowledge and understanding: Student:

Understands the difference between scientific and system approach

The student understands the Aristotels rule

The student has the competencies in system

http://www.amazon.com/gp/product/1843761971/sr=8-15/qid=1147505459/ref=sr_1_15/102-7687267-0241708?%5Fencoding=UTF8

sistemov, teorije kompleksnosti in teorije kaosa

Študent ima kompetence da naučene teorije uporabi v praktičnih primerih iz bioinformatike

theory, soft system theory, theory of complexity and chaos theory

Students is able to use the above theories in practical applications in bioinformatics



Predavanja, seminarji, delavnice.

Lectures, seminar work, workshops.



Assessment:

Način (pisni izpit, ustno izpraševanje, naloge, projekt) Kolokviji Pisni izpit Projekt.

30 20 50

Type (examination, oral, coursework, project): Kolokviji Pisni izpit Projekt.


EVOLUTIONARY design of decision trees for medical application [Elektronski vir] / Peter Kokol ... [et al.]. - Soavtorji: Sandi Pohorec, Gregor Štiglic, Vili Podgorelec. - Bibliografija: str. 252-254. V: Wiley interdisciplinary reviews. Data mining and knowledge discovery [Elektronski vir]. - ISSN 1942-4795. - Vol. 2, iss. 3 (May 2012), str. 237-254. . - doi: 10.1002/widm.1056 COBISS.SI-ID 15997462 KOKOL, Peter, 1957- Intelligent system supported evidence based management [Elektronski vir] / Peter Kokol, Gregor Štiglic. - ilustr. - Bibliografija: str. 198. - Abstract. V: CAINE-2011 [Elektronski vir] / 24th International Conference on Computers and Their Applications in Industry and Engineering November 16-18, 2011, Honolulu, HI USA. - Cary, NC : ISCA, 2011. - ISBN 978-1-880843-83-3. - Str. 195-198.COBISS.SI-ID 1764516 COMPUTATIONAL complexity : theory, techniques, and applications / editor-in-chief, Robert A. Meyers. - New York : Springer, cop. 2012. - 6 zv. (XLIV, 3492 str.) ISBN 1-4614-1799-6 (hbk) ISBN 978-1-4614-1799-6 (hbk.) COBISS.SI-ID 1780644


Predmet: Vizualizacija znanstvenih podatkov

Course title: Scientific Visualisation




Semester Semester



Bioinformatics 2 3



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial




ECTS

15 30 105 6

Nosilec predmeta / Lecturer: doc. dr. Domen Mongus

Jeziki / Languages:




Prerequisits:

Osnovna programerska znanja in poznavanje osnov algoritmov ter podatkovnih struktur.

Basic programming skills and basic knowledge of algorithms and data structures.

Vsebina:


Uvod: namen in cilji vizualizacije znanstvenih podatkov, zgodovinski pregled, modeli za znanstveno vizualizacijo, simulacija, animacija in navidezna resničnost.

Osnove računalniške grafike in geometrijskega modeliranja: tehnike predstavitve geometrijskih objektov, geometrijske transformacije, projekcije, osnove upodabljanja.

Vizualizacija informacij: 1D, 2D, 3D in 4D podatki, risanje dreves, mrež in grafov, interakcija z drevesi in grafi, skalarna in vektorska polja, “nefotorealistično” upodabljanje.

Vizualizacija ploskovnih in volumetričnih podatkov: vizualizacija površja, direktno upodabljanje vokselskih podatkov, posredno upodabljanje vzorčenih objektov z

Introduction: why scientific visualisation, historical overview, models for scientific visualization, simulation, animation and virtual reality.

Fundamentals of computer graphics and geometric modelling: different representations of geometric objects, geometric transformations, projections, basic principles of rendering.

Information visualisation: 1D, 2D, 3D and 4D data, plotting trees, grids, and graphs, graphs and trees interactions, scalar and vector fields, non-photorealistic rendering.

Surface visualisation and visualization of volumetric data: surface rendering, direct visualisation of voxel data, indirect visualization of sampled objects by surface reconstruction.

Applications of scientific visualisation:

rekonstrukcijo površja.

Aplikacije znanstvene vizualizacije: vizualizacija kemijskih struktur v biologiji, kemiji in fiziki, vizualizacija pretakanja tekočin, geografska, geološka in meteorološka vizualizacija, vizualizacija v medicini.

Vizualizacija v bioinformatiki: modeliranje in vizualizacija molekul, vizualizacija anatomije, vizualizacija sekvenc DNA .

Programska oprema za vizualizacijo v bioinformatiki: pregled in uporaba programskih paketov za vizualizacijo struktur v bioinformatiki (Cn3D, Rasmol, Protein Explorer, Chime), analiza in primerjava paketov.

visualisation of chemical structures in biology, chemistry and physics, fluid visualisation, geographic, geological and meteorological visualization, medical visualisation.

Bioinformatics visualization: molecular modelling, anatomic visualization, visualization of DNA sequences.

Software for bioinformatics visualization: a survey and use of software packages for structure visualization in bioinformatics (Cn3D, Rasmol, Protein Explorer, Chime), analysis and comparison of packages.


1. Chaomei Chen: Information Visualization. Springer; 2 edition, 2004. ISBN: 1852337893. 2. Michael Jünger (Editor), Petra Mutzel (Editor): Graph Drawing Software. Springer, 2003. ISBN:

3540008810. 3. Isaac Bankman: Handbook of Medical Imaging: Processing and Analysis. Academic Press; 2000.

ISBN: 0120777908. 4. Wen Jei Yang: Handbook of Flow Visualization. Taylor & Francis, 2nd edition, 2001. ISBN:

1560324171.



Cilj tega predmeta je obogatiti študentove praktične izkušnje rabe vizualizacije, organizirati, formalizirati in predvsem razširiti njegovo znanje o vizualizaciji s teoretskim ozadjem, s podatkovnimi tipi in algoritmi ter ga tako usposobiti za učinkovitejšo rabo, za razvoj in implementacijo sistemov za vizualizacijo znanstvenih podatkov.

Spretnosti komuniciranja: ustno izražanje pri ustnem izpitu in zagovoru laboratorijskih vaj, pisanje poročila o opravljenem projektu.

Uporaba informacijske tehnologije: uporaba sodobnih programov za vizualizacijo v bioinformatiki, sodobnih orodij za razvoj programske opreme in posebnih programskih knjižnic za vizualizacijo.

Reševanje problemov: samostojno delo na projektu.

The objective of this course is to enrich student’s experience in using visualisation, to organize, to formalize and to widen his knowledge of visualisation by learning the theoretical background, data types and algorithms and, consequently, to qualify him for more efficient use, development and implementation of scientific visualisation systems.

Communication skills: oral manner of expression at oral exemination and lab work defense, writing report about completed project.

Use of information technology: use of present software for bioinformatics visualisation, present software development tools and special visualisation libraries.

Problem solving: individual project work.



Znanje in razumevanje: Po zaključku tega predmeta bo študent sposoben:

- izkazati poglobljeno znanje o principih, podatkovnih strukturah in algoritmih vizualizacije,

Knowledge and understanding: On completion of this course the student will be able to:

- demonstrate broad knowledge of visualisation principles, data types and

- izbrati ustrezno tehniko predstavitve in vizualizacije podatkov pri reševanju resničnih znanstvenih in inženirskih problemov,

- uporabiti teoretična znanja in praktične izkušnje pri učinkoviti rabi programske opreme za vizualizacijo v bioinformatiki,

- ovrednotiti uporabljivost obstoječe programske opreme v dani praktični situaciji in po potrebi načrtovati in implementirati lasten sistem.

- navesti in ilustrirati rabo znanstvene vizualizacije tudi na nekaterih drugih področjih (medicina, geografija, geologija, meteorologija...)

algorithms, - select a proper representation and

visualisation technique for soliving real scientific and engineering problems,

- use theoretical knowledge and practical experience for eficient use of visualisation software in bioinformatics,

- evaluate applicability of existing software in a given practical situation and, as necessary, design and implement own system,

- list and illustrate use of scientific visualisation in some other fields (medicine, geography, geology, meteorology...).




Lectures, discussions, demonstration, computer exercises.



Assessment:

Način (pisni izpit, ustno izpraševanje, naloge, projekt) - Naloge (računalniške vaje) - projekt (seminarska naloga), - ustni izpit.

30 20 50

Type (examination, oral, coursework, project): - coursework (computer exercises ) - projects (seminary work) - oral examination.


MONGUS, Domen, REPNIK, Blaž, MERNIK, Marjan, ŽALIK, Borut. A hybrid evolutionary algorithm for tuning a cloth-simulation model. Applied soft computing, Jan. 2012, vol. 12, iss. 1, str. 266-273, doi: 10.1016/j.asoc.2011.08.047. [COBISS.SI-ID 15310102], [JCR, WoS do 6. 10. 2012: št. citatov (TC): 1, čistih citatov (CI): 1, normirano št. čistih citatov (NC): 1, Scopus do 12. 7. 2012: št. citatov (TC): 1, čistih citatov (CI): 1, normirano št. čistih citatov (NC): 1] MONGUS, Domen, ŽALIK, Borut. Parameter-free ground filtering of LiDAR data for automatic DTM generation. ISPRS j. photogramm. remote sens.. [Print ed.], 2012, vol. 67, str. 1-12, ilustr., doi: 10.1016/j.isprsjprs.2011.10.002. [COBISS.SI-ID 15485718], [JCR, WoS do 6. 11. 2012: št. citatov (TC): 1, čistih citatov (CI): 1, normirano št. čistih citatov (NC): 1, Scopus do 2. 1. 2013: št. citatov (TC): 2, čistih citatov (CI): 1, normirano št. čistih citatov (NC): 3] MONGUS, Domen, ŽALIK, Borut. Efficient method for lossless LIDAR data compression. Int. j. remote sens. (Print). [Print ed.], 2011, vol. 32, no. 9, str. 2507-2518, doi: 10.1080/01431161003698385. [COBISS.SI-ID 14953494], [JCR, WoS do 6. 12. 2012: št. citatov (TC): 1, čistih citatov (CI): 0, normirano št. čistih citatov (NC): 0, Scopus do 20. 2. 2013: št. citatov (TC): 5, čistih citatov (CI): 2, normirano št. čistih citatov (NC): 1]


Predmet: Zdravstvena informatika

Course title: Health informatics




Semester Semester



Bioinformatics 2 3



Predavanja Lectures

Seminar Seminar

Sem. vaje Tutorial




ECTS

15 30 105 6

Nosilec predmeta / Lecturer: Prof. dr. Kokol Peter, prof. dr. Tatjana Welzer Družovec

Jeziki / Languages:




Prerequisits:

Znanja s področja računalništva in informatike.

Knowledge in computer science and informatics.

Vsebina:


- Informatika v zdravstvu in zdravstveni negi. - Inžinering zahtev, načrtovanje, modeliranje

in implementacija informacijskih sistemov - Baze podatkov v bionformatiki in

zdravstvu - Zagotavljanje kvalitete informacijskih

sistemov za zdravstvo in zdravstveno nego - Inteligentni sistemi. - Odločitvena drevesa v zdravstvu in

zdravstveni negi - Telemedicina - Pomen informatike pri organizaciji

delovnega procesa v zdravstvenih sistemih

- Health and nursing informatics - Requirements engineering, information

system development, implementation. - Databases in bioinformatics and health - Quality assurance of hospital information

systems for health and nursing - Intelligent systems - Decision trees in health and nursing - Telemedicine - Informatics in organization and working

processes in health systems


1. M.J. Ball et all. Nursing Informatics: Where carring and Technology Meet. 3rd ed./ New York: Springer-Verlag, 2000.

2. L. Burke, B. Weill. Information Technology for the Health Professions. 2nd ed./ Prentice Hall, 2004. 3. E. Turban et all. Introduction to Information Technology. 3rd ed./ Wiley, 2004 4. Kokol P. Računalništvo v zdravstvo I. Maribor: Visoka zdravstvena šola, 1998 NICE textbooks from

the Phare Tempus program. 5. Saba VK, McCormick A. Essentials of Nursing Informatics, IOS Press, 2005.



Študent:

bo sposoben/a aktivno sodelovati pri razvoju informacijskih sistemov v zdravstvu in zdravstveni negi

Student: - will be capable to take an active part in

hospital information systems development.




pozna pomembnosti informacije, informacijskih sistemov in informacijske tehnologijev zdravstvu in zdravstveni negi;

razume pomembnost vloge vodilnih medicinskih sester pri razvoju informacijskih sistemov zdravstvene negi

zna uporabljati teorijo razvoja informacijskih sistemov zdravstvene nege v praksi

Knowledge and understanding: - understands the importance of information,

information systems and information technology in health and nursing care;

- understands the importance of nursing leaders in process of nursing information systems development;

- is able to use theory and practice of information systems development



Predavanja, seminarji, delavnice.

Lectures, seminar work, workshops.



Assessment:

Način (pisni izpit, ustno izpraševanje, naloge, projekt) Pisni izpit, projekt.

40 60

Type (examination, oral, coursework, project): Written exam, project.


EVOLUTIONARY design of decision trees for medical application [Elektronski vir] / Peter Kokol ... [et al.]. - Soavtorji: Sandi Pohorec, Gregor Štiglic, Vili Podgorelec. - Bibliografija: str. 252-254. V: Wiley interdisciplinary reviews. Data mining and knowledge discovery [Elektronski vir]. - ISSN 1942-4795. - Vol. 2, iss. 3 (May 2012), str. 237-254. . - doi: 10.1002/widm.1056 COBISS.SI-ID 15997462 KOKOL, Peter, 1957- Intelligent system supported evidence based management [Elektronski vir] / Peter Kokol, Gregor Štiglic. - ilustr. - Bibliografija: str. 198. - Abstract. V: CAINE-2011 [Elektronski vir] / 24th International Conference on Computers and Their Applications in Industry and Engineering November 16-18, 2011, Honolulu, HI USA. -

http://www.amazon.com/gp/product/0071441972/sr=8-1/qid=1145800908/ref=pd_bbs_1/103-0765209-6154227?%5Fencoding=UTF8

Cary, NC : ISCA, 2011. - ISBN 978-1-880843-83-3. - Str. 195-198.COBISS.SI-ID 1764516 COMPUTATIONAL complexity : theory, techniques, and applications / editor-in-chief, Robert A. Meyers. - New York : Springer, cop. 2012. - 6 zv. (XLIV, 3492 str.) ISBN 1-4614-1799-6 (hbk) ISBN 978-1-4614-1799-6 (hbk.) COBISS.SI-ID 1780644 VIRTUAL education centre for the development of expert skills and competencies [Elektronski vir] / Tatjana Welzer ... [et al.]. - Nasl. z nasl. zaslona. - Opis vira z dne 21. 11. 2011. - Bibliografija: str. 54. - Abstract. V: International journal of advanced corporate learning [Elektronski vir]. - ISSN Y505-6985. - Vol. 4, no. 4 (2011), str. 51-54. - doi: ijac.v4i4.1747 COBISS.SI-ID 15528726 HÖLBL, Marko Two improved two-party identity-based authenticated key agreement protocols / Marko Hölbl, Tatjana Welzer. V: Computer standards & interfaces. - ISSN 0920-5489.. - Vol. 31, iss. 6 (Nov. 2009), str. 1056-1060. . - doi: 10.1016/j.csi.2008.09.024 COBISS.SI-ID 13379606, JCR, WoS, št. citatov do 6. 6. 2012: 3, brez avtocitatov: 3, normirano št. citatov: 2 WELZER-Družovec, Tatjana Culture sensitive aspects in informatics education [Elektronski vir] / Tatjana Welzer, Marjan Družovec, Hannu Jaakkola. - Ilustr. - Bibliografija na koncu prispevka. - Abstract. V: EAEEIE2012 [Elektronski vir] / 23rd EAEEIE annual conference, Cagliary, Italy, February 26-27, 2012. - [S. l. : s. n.], cop. 2012. - Str. 1-3. COBISS.SI-ID 15829270

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