The two-regime method for optimizing stochastic reaction-diffusion simulations

M. B. Flegg, S. J. Chapman, R. Erban

Research output: Contribution to journalArticlepeer-review

78 Scopus citations

Abstract

Spatial organization and noise play an important role in molecular systems biology. In recent years, a number of software packages have been developed for stochastic spatio-temporal simulation, ranging from detailed molecular-based approaches to less detailed compartment-based simulations. Compartment-based approaches yield quick and accurate mesoscopic results, but lack the level of detail that is characteristic of the computationally intensive molecular-based models. Often microscopic detail is only required in a small region (e.g. close to the cell membrane). Currently, the best way to achieve microscopic detail is to use a resource-intensive simulation over the whole domain. We develop the two-regime method (TRM) in which a molecular-based algorithm is used where desired and a compartment-based approach is used elsewhere. We present easy-to-implement coupling conditions which ensure that the TRM results have the same accuracy as a detailed molecular-based model in the whole simulation domain. Therefore, the TRM combines strengths of previously developed stochastic reaction-diffusion software to efficiently explore the behaviour of biological models. Illustrative examples and the mathematical justification of the TRM are also presented.
Original languageEnglish (US)
Pages (from-to)859-868
Number of pages10
JournalJournal of the Royal Society Interface
Volume9
Issue number70
DOIs
StatePublished - Oct 19 2011
Externally publishedYes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUK-C1-013-04
Acknowledgements: The research leading to these results has received funding from the European Research Council under the European Community's Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no. 239870. This publication was based on work supported in part by award no. KUK-C1-013-04, made by the King Abdullah University of Science and Technology (KAUST). R.E. would also like to thank Somerville College, University of Oxford, for a Fulford Junior Research Fellowship.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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