A study of parallel and evolutionary framework for modelling biochemical signalling pathways

Modelling biochemical pathways provides an opportunity for scientists and engineers from biochemistry, computer science and mathematics areas to work together in the area of computational biology. Due to the complexity of biochemical pathways, it is natural to employ a parallel and evolutionary modelling approach to composing target biochemical signalling pathways. In this research, a parallel and evolutionary modelling framework is proposed to construct models for biochemical pathways. An evolutionary method is employed to develop biochemical components by generic operators and suggested composition rules, and then a global search approach is used to explore kinetic rate values in the model candidates. Information of species behaviours and interactions among the species in given target biochemical pathways is referred to drive the model constructions. Simulation results show that the modelling framework is feasible to explore the biochemical model structure space and obtain biochemical reactants performing discover of biochemical elements in the target pathways. evolution strategy; simulated annealing.