Tehnisko un bioloģisko
sistēmu paaudžu mēroga
dzīves ciklu salīdzinājums
Dr.sc.ing. Egils Stalidzans
Biosistēmu grupa
Informācijas Tehnoloģiju fakultāte
Latvijas Lauksaimniecības Universitāte
www.biosystems.lv
1
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 (sometimes optimal) strategies of
repairs, improvements and forecasts of their side effects
are possible.
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 strategies of repairs, improvements
and forecasts of their side effects are exceptions.
2
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.
3
Source: Wikipedia
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!
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.
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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).
Technical
system
Goals and
tasks
Biological
system
Survive and
reproduce
Pool of
designs
Pool of
genomes
ACS + object
BCS within
biol. object
Behaviour
Death
Feedback
to next
generation
Behaviour
Feedback
to next
generation
Death
8
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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ACS lifecycle
BCS lifecycle
Goals and
tasks
Survive and
reproduce
Design
ACS
influenced
Genome
ACS +
Feedback
BCS within
ACS
influenced
biol. object
ACS
influenced
behaviour
ACS
influenced
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!
14
Paldies!
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