Literature DB >> 19700812

Stochastic modelling of reaction-diffusion processes: algorithms for bimolecular reactions.

Radek Erban1, S Jonathan Chapman.   

Abstract

Several stochastic simulation algorithms (SSAs) have recently been proposed for modelling reaction-diffusion processes in cellular and molecular biology. In this paper, two commonly used SSAs are studied. The first SSA is an on-lattice model described by the reaction-diffusion master equation. The second SSA is an off-lattice model based on the simulation of Brownian motion of individual molecules and their reactive collisions. In both cases, it is shown that the commonly used implementation of bimolecular reactions (i.e. the reactions of the form A + B --> C or A + A --> C) might lead to incorrect results. Improvements of both SSAs are suggested which overcome the difficulties highlighted. In particular, a formula is presented for the smallest possible compartment size (lattice spacing) which can be correctly implemented in the first model. This implementation uses a new formula for the rate of bimolecular reactions per compartment (lattice site).

Mesh:

Year:  2009        PMID: 19700812     DOI: 10.1088/1478-3975/6/4/046001

Source DB:  PubMed          Journal:  Phys Biol        ISSN: 1478-3967            Impact factor:   2.583


  73 in total

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7.  Editorial: special issue on stochastic modelling of reaction-diffusion processes in biology.

Authors:  Radek Erban; Hans G Othmer
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8.  An accelerated algorithm for discrete stochastic simulation of reaction-diffusion systems using gradient-based diffusion and tau-leaping.

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Journal:  J Chem Phys       Date:  2011-04-21       Impact factor: 3.488

9.  Dynamic transition states of ErbB1 phosphorylation predicted by spatial stochastic modeling.

Authors:  Meghan McCabe Pryor; Shalini T Low-Nam; Adám M Halász; Diane S Lidke; Bridget S Wilson; Jeremy S Edwards
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10.  Stochastic simulation of structured skin cell population dynamics.

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Journal:  J Math Biol       Date:  2012-12-20       Impact factor: 2.259

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