Modeling and evolving biochemical networks: insights into
communication and computation from the biological domain
Decraene, James, Mitchell, George G. and McMullin, BarryORCID: 0000-0002-5789-2068
(2008)
Modeling and evolving biochemical networks: insights into
communication and computation from the biological domain.
In: CIICT 2008: China-Ireland International Conference on Information and Communications Technologies, 26-28 September 2008, Beijing, China.
ISBN 9780863419218
This paper is concerned with the modeling and evolving
of Cell Signaling Networks (CSNs) in silico. CSNs are
complex biochemical networks responsible for the coordination of cellular activities. We examine the possibility to computationally evolve and simulate Artificial Cell Signaling Networks (ACSNs) by means of Evolutionary Computation techniques. From a practical point of view, realizing and evolving ACSNs may provide novel computational paradigms for a variety of application areas. For example, understanding some inherent properties of CSNs such as crosstalk may be of interest: A potential benefit of engineering crosstalking systems is that it allows the modification of a specific process according to the state of other processes in the system. This is clearly necessary in order to achieve complex control tasks. This work may also contribute to the biological understanding of the origins and evolution of real CSNs. An introduction to CSNs is first
provided, in which we describe the potential applications
of modeling and evolving these biochemical networks in
silico. We then review the different classes of techniques to model CSNs, this is followed by a presentation of two alternative approaches employed to evolve CSNs within the
ESIGNET project. Results obtained with these methods
are summarized and discussed.