Discrete Event Modeling and Simulation in Systems Biology

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Roland Ewald, Carsten Maus, Arndt Rolfs, Adelinde M. Uhrmacher
Journal of Simulation 1(2), pages 81-96
May 2007

With Systems Biology, a promising new application area for modeling and simulation emerges. Today's biologists are facing huge amounts of data delivered at different levels of detail by a multitude of advanced experimentation techniques. The Systems Biology approach copes with this information by cycling through phases of forming hypothesis, constructing models, experimenting with or analyzing these models, and validating the findings by wet-lab experiments. A crucial point is therefore the way in which the knowledge about a system is formalized, i.e., how a biological system is described as this constrains the perception of the system as well as scope of possible answers the model might provide. In this article, we compare different discrete-event modeling formalisms (Petri Nets, Stochastic Pi-Calculus , StateCharts, and Devs) regarding their applicability to a cell biological system of current research interest, the Wnt signaling pathway. We then introduce the popular Gillespie algorithm, which is the foundation of many discrete-event simulators for molecular-biological systems, and elaborate on some interesting extensions.

keywordsdiscrete event modelling formalisms, discrete event simulation, systems biology, stochastic simulation, Petri Nets, Stochastic pi-Calculus
journal or series
book Journal of Simulation (JOS)