Efficient Stochastic Simulation of Biological Systems with Multiple Variable Volumes
Electronic Notes in Theoretical Computer Science (ENTCS)
Stochastic biological modelling in the presence of multiple compartments
Theoretical Computer Science
Stochastic simulation of biological systems with dynamical compartment structure
CMSB'07 Proceedings of the 2007 international conference on Computational methods in systems biology
Stochastic Petri net models of Ca2+ signaling complexes and their analysis
Natural Computing: an international journal
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Realistic simulations of the biological systems evolution require a mathematical model of the stochasticity of the involved processes and a formalism for specifying the concurrent nature of the biochemical interactions. The Gillespie algorithm is a well-established stochastic algorithm satisfying the first requirement. The second requirement can be satisfied by the π-calculus, a process algebra used in computer science for describing interactions between simultaneously running processes. Its stochastic variant has been recently applied to the specification of the biological systems.This paper shows how to generalize the Gillespie algorithm by letting the reaction propensity be a function of time. In particular, the work formulates those modifications necessary when the time dependence of the reaction propensity is due to changes either of volume or temperature. This re-formulation has been then adapted to be incorporated in the framework of stochastic π-calculus and has been applied to a sample simulation in biology: the passive glucose cellular transport.