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 language | English (US) |
---|---|
Pages (from-to) | 859-868 |
Number of pages | 10 |
Journal | Journal of the Royal Society Interface |
Volume | 9 |
Issue number | 70 |
DOIs | |
State | Published - Oct 19 2011 |
Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledged 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.