Effective stochastic simulation methods for chemical reaction systems

Recent studies through biological experiments have indicated that noise plays a very important role in determining the dynamic behaviour of biological systems. The advances in stochastic modelling of genetic regulatory networks and cell signalling transduction pathways have proposed chemical reaction systems in which some key reactants have small copy numbers. Over the last years extensive research has been carried out to develop effective τ-leap methods and multiscale simulation methods to reduce the huge computational time of the stochastic simulation algorithm. This paper gives a review of the recent progress in the stochastic simulation methods for chemical reaction systems