Stochastic Simulation Techniques in Systems Biology

Biological modeling to gain system-level understanding of disease mechanisms, and to identify new drug targets has been gaining increasing attention due to remarkable advances in fields like molecular biology and genetics. Understanding system dynamics is a key component necessary to gain insight for this system-level approach. Often, the behavior of reactant biochemical species participating in system dynamics is inherently stochastic in nature, and needs to be taken into account to reliably predict random variations in switching mechanisms in biological pathways, production of biochemical species, phenotypes, morphology etc. This survey paper reviews various stochastic simulation techniques used in systems biology to predict such behavior.