The two-regime method for optimizing stochastic reaction-diffusion simulations
KAUST Grant NumberKUK-C1-013-04
Permanent link to this recordhttp://hdl.handle.net/10754/599972
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AbstractSpatial 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.
CitationFlegg MB, Chapman SJ, Erban R (2011) The two-regime method for optimizing stochastic reaction-diffusion simulations. Journal of The Royal Society Interface 9: 859–868. Available: http://dx.doi.org/10.1098/rsif.2011.0574.
SponsorsThe 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.
PublisherThe Royal Society
PubMed Central IDPMC3306650
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