Tehnisko un bioloģisko sistēmu paaudžu mēroga

dzīves ciklu salīdzinājums

Dr.sc.ing. Egils Stalidzans

Biosistēmu grupa

Informācijas Tehnoloģiju fakultāte

Latvijas Lauksaimniecības Universitāte

1www.biosystems.lv

State of the art (current achievements) in the modelling of technical and biological systems (1)Technical systems:- full quantitative dynamic cause-effect models from elements up to a functioning system are possible

Conclusion: rational strategies of repairs, improvements and forecasts of their side effects are exceptions.

Biological systems:- quite good information on the level of organs and modules,- some information about elements (on molecular level),- some information about some cause-effect relationships between elements in some cases

Conclusion: rational (sometimes optimal) strategies of repairs, improvements and forecasts of their side effects are possible.

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What are the reasons for different status of modelling achievements in technical and biological systems?

They are very different (elements, authors and many other things). Do they have something in common?

Cybernetics was defined by Norbert Wiener, in his book (1948) of that title, as the study of control and communication in the animal and the machine.

It includes the study of feedback, black boxes and derived concepts such as communication and control in living organisms, machines and organisations including self-organisation. Its focus is how anything (digital, mechanical or biological) processes information, reacts to information, and changes or can be changed to better accomplish the first two tasks.

Source: Wikipedia3

Why and how biological and technical systems evolve and disappear?

Can we compare their life cycles?

YES, they have some things in common!

Both biological and technical systems have evolutionary pressure in multigeneration lifecycle. Their survival is assured by different technologies!

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Mozga et. al. (2007) Life cycles and competition in modelling of artificial and biological control systems. European Simulation and Modelling Conference, St. Julians, Malta, Oct.22-24.

Stable active technical system

Stable active biological system

Artificial control system (ACS) is a human designed control system. It can be executed by technical,

chemical, biological or other means.

- technical control system (climate control system in a building, control system of an aircraft), - control system for natural non biological objects (irrigation systems), - human made control system of biological objects (fermentation process control), - human designed control of biological object by another biological object (pest control by purposeful introduction of their biological enemies).

Biological control system (BCS) is in biological reproduction process developed control system that

ensures internal processes within biological object and interaction

processes with environment. Features of biological objects are metabolism and reproduction.

BCS controlled biological objects are for example all living organisms (plants, animals, humans) as well as their subsystems (body temperature control, metabolism, processes within a cell).

Goals and tasks

Pool of designs

Behaviour

Survive andreproduce

Pool of genomes

BCS within biol. object

Behaviour

ACS + object

Feedback to next

generation

Feedbackto next

generation

Technical system

Biological system

Death Death

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The lifecycle of technical system includes: 1)definition of targets, 2)design of control system and object, 3)execution of technical control system, 4)behaviour of technical object as observable result,5)feedback to the design.

The lifecycle of biological system has corresponding steps in different execution and includes: 1)predefined targets (survival and reproduction), 2)genome (as design of control system), 3)cells and organism (as execution of biological control system), 4)behaviour of biological object as observable result,5)feedback to genome (as design of control system).

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Differences in execution

Single design language of BCS Low cost live testing of new designs of

BCS enables stochastic design due to biosystems ability to grow

No need for technical documentation of design for author or users (stochastic design) in case of BCS

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Conclusion: lifecycles in multigeneration scale of biological and technical systems are quite similar while execution mechanisms are very different.

Conclusion: one can apply the same principles to develop control of biosystems to the level of control of technical systems.

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Artificial control of biological objects

oVia environment without changes in biological control system (BCS) – shift of evolutionary presure: household animals and plants

oVia direct genetic changes of BCS (implementation of artificial control system (ACS) into BCS): metabolic engineering, GMO

Changes in the genome is the result in both cases.

Good? Bad?

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Goals and tasks

ACS lifecycle

Design

Survive and reproduce

BCS lifecycle

ACS influenced

Genome

BCS withinACS

influenced biol. object

ACS influencedbehaviour

ACS +

ACS influencedfeedback

Feedback

Lifecycle of meld ACS and BCS during control of biological objects. Colored area is the influenced part of BCS cycle.

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Systems biology: can we explain the opperation of the BCS of an organism?

“Yes” means: we have a model!

Syntetic biology: how should we change the BCS to get the needed behavior?

“How” means: we know the components which have to be implemented in the system. Would be nice to test them on a model in advance!

Paldies!

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