Briefings in Bioinformatics Advance Access originally published online on January 16, 2009
Briefings in Bioinformatics 2009 10(1):53-64; doi:10.1093/bib/bbn050
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Biochemical simulations: stochastic, approximate stochastic and hybrid approaches
Corresponding author. Jürgen Pahle, Bioquant/Institute of Zoology, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany. Tel: +49 6221 5451277; Fax: +49 6221 5451483; E-mail: juergen.pahle{at}bioquant.uni-heidelberg.de
Computer simulations have become an invaluable tool to study the sometimes counterintuitive temporal dynamics of (bio-)chemical systems. In particular, stochastic simulation methods have attracted increasing interest recently. In contrast to the well-known deterministic approach based on ordinary differential equations, they can capture effects that occur due to the underlying discreteness of the systems and random fluctuations in molecular numbers. Numerous stochastic, approximate stochastic and hybrid simulation methods have been proposed in the literature. In this article, they are systematically reviewed in order to guide the researcher and help her find the appropriate method for a specific problem.
Keywords: stochastic simulation, biochemical systems, approximate stochastic simulation, hybrid simulation methods, systems biology
Submitted: July 1, 2008. Received (in revised form): October 13, 2008.