Reliable regulatory dynamics from network evolution
Abstract Book of the XXIII IUPAP International Conference on Statistical Physics, Genova, Italy, (9-13 July 2007)Abstract
Living organisms have to function reliably in spite of the molecular fluctuations that are omnipresent in biochemical systems. This is a necessary requirement for survival and thus for selection in an evolutionary setting. On the other hand, it is still largely unknown how intricate networks of stochastic components can work together in a way that their outcome is dependable. In a simple Boolean model we investigate how the structure of a network as a whole can account for reliability.
Reliability of a limit cycle attractor can be defined as the ability of a system to function in a quasi-deterministic fashion despite noisy transmission times. We introduce an evolutionary process that selects networks for reliability by a simple deterministic criterion. We find that our evolutionary process can quickly drive networks to reliability by significantly changing the structure of the attractor landscape. We also find that with high probability a network with a given `functional' attractor can be made reliable while retaining this attractor.