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    Adaptive simulation of hybrid stochastic and deterministic models for biochemical systems

    Alfonsi, Aurélien and Cancès, Eric and Turinici, Gabriel and Di Ventura, Barbara and Huisinga, Wilhelm (2005) Adaptive simulation of hybrid stochastic and deterministic models for biochemical systems. ESAIM: Proceedings, 14 (September). pp. 1-13. ISSN 1270-900X

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    In the past years it has become evident that stochastic effects in regulatory networks play an important role, leading to an increasing in stochastic modelling attempts. In contrast, metabolic networks involving large numbers of molecules are most often modelled deterministically. Going towards the integration of different model systems, gen-regulatory networks become part of a larger model system including signalling pathways and metabolic networks. Thus, the question arises of how to efficiently and accurately simulation such coupled or hybrid systems. We present an algorithmic approach for the simulation of hybrid stochastic and deterministic reaction models that allows for adaptive step-size integration of the deterministic equations while at the same time accurately tracing the stochastic reaction events. We present a mathematical derivation of the hybrid system on the stochastic process level, and present numerical examples that outline the power of hybrid simulations.

    Item Type: Article
    Additional Information: Proceedings of CEMRACS 2004 - Mathematics and applications to biology and medicine Marseille, France, July 26 - September 3, 2004
    Keywords: Stochastic models; Deterministic models; Algorithmic realization; Hybrid models.
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Faculty of Science and Engineering > Mathematics and Statistics
    Item ID: 1821
    Identification Number:
    Depositing User: Hamilton Editor
    Date Deposited: 27 Jan 2010 16:03
    Journal or Publication Title: ESAIM: Proceedings
    Publisher: EDP Sciences
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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