The two-regime method for optimizing stochastic reaction-diffusion simulations
KAUST Grant NumberKUK-C1-013-04
Online Publication Date2011-10-19
Print Publication Date2012-05-07
Permanent link to this recordhttp://hdl.handle.net/10754/599972
MetadataShow full item record
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
CollectionsPublications Acknowledging KAUST Support
- URDME: a modular framework for stochastic simulation of reaction-transport processes in complex geometries.
- Authors: Drawert B, Engblom S, Hellander A
- Issue date: 2012 Jun 22
- Convergence of methods for coupling of microscopic and mesoscopic reaction-diffusion simulations.
- Authors: Flegga MB, Hellander S, Erban R
- Issue date: 2015 May 15
- Algorithm for Mesoscopic Advection-Diffusion.
- Authors: Noel A, Makrakis D
- Issue date: 2018 Oct
- A hybrid method for micro-mesoscopic stochastic simulation of reaction-diffusion systems.
- Authors: Sayyidmousavi A, Rohlf K, Ilie S
- Issue date: 2019 Jun
- MONALISA for stochastic simulations of Petri net models of biochemical systems.
- Authors: Balazki P, Lindauer K, Einloft J, Ackermann J, Koch I
- Issue date: 2015 Jul 10