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Exact simulation of hybrid stochastic and deterministic models for biochemical systems

Abstract : Motivation : Over the last years it has become evident that stochastic effects play an important role in biological processes leading to an increase in stochastic modelling attempts. Despite the availability of exact algorithms to numerically solve the chemical master equation that entirely describes a stochastic system, stochastic simulations are most of the times very computationally expensive. Hybrid methods that treat some processes as in the deterministic framework and others as stochastic are a promising way to speed up simulations for those cases involving different time scales, e.g., systems integrating metabolic pathways and gene regulatory networks.
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https://hal.inria.fr/inria-00070572
Contributor : Rapport de Recherche Inria <>
Submitted on : Friday, May 19, 2006 - 8:54:49 PM
Last modification on : Friday, November 29, 2019 - 1:08:05 PM
Long-term archiving on: : Sunday, April 4, 2010 - 9:29:33 PM

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  • HAL Id : inria-00070572, version 1

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Aurélien Alfonsi, Eric Cancès, Gabriel Turinici, Barbara Di Ventura, Wilhelm Huisinga. Exact simulation of hybrid stochastic and deterministic models for biochemical systems. [Research Report] RR-5435, INRIA. 2004, pp.20. ⟨inria-00070572⟩

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