"Evolving Genetic Regulatory Networks Performing as Oscillators and Switches in the Stochastic Regime"

Recent studies have shown that small genetic regulatory networks (GRNs) can be evolved in silico displaying certain dynamics in the underlying mathematical model. To take the stochastic nature of GRNs into account, our evolutionary approach models GRNs as biochemical reaction networks based on simple enzyme kinetics and simulates them by using Gillespie's stochastic simulation algorithm (SSA). The relevance of considering intrinsic stochasticity is demonstrated by GRNs which show certain dynamics in the SSA but not in the ODE regime. First results in the evolution of GRNs performing as stochastic oscillators and switches are presented. It is expected that evolutionary approaches can help to gain a better understanding of biological design principles and to assist in synthetic biology.