Literature DB >> 22680526

Reaction-diffusion master equation in the microscopic limit.

Stefan Hellander1, Andreas Hellander, Linda Petzold.   

Abstract

Stochastic modeling of reaction-diffusion kinetics has emerged as a powerful theoretical tool in the study of biochemical reaction networks. Two frequently employed models are the particle-tracking Smoluchowski framework and the on-lattice reaction-diffusion master equation (RDME) framework. As the mesh size goes from coarse to fine, the RDME initially becomes more accurate. However, recent developments have shown that it will become increasingly inaccurate compared to the Smoluchowski model as the lattice spacing becomes very fine. Here we give a general and simple argument for why the RDME breaks down. Our analysis reveals a hard limit on the voxel size for which no local RDME can agree with the Smoluchowski model and lets us quantify this limit in two and three dimensions. In this light we review and discuss recent work in which the RDME has been modified in different ways in order to better agree with the microscale model for very small voxel sizes.

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Year:  2012        PMID: 22680526     DOI: 10.1103/PhysRevE.85.042901

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  25 in total

1.  Theory of bi-molecular association dynamics in 2D for accurate model and experimental parameterization of binding rates.

Authors:  Osman N Yogurtcu; Margaret E Johnson
Journal:  J Chem Phys       Date:  2015-08-28       Impact factor: 3.488

2.  Reaction rates for a generalized reaction-diffusion master equation.

Authors:  Stefan Hellander; Linda Petzold
Journal:  Phys Rev E       Date:  2016-01-19       Impact factor: 2.529

3.  Single molecule simulations in complex geometries with embedded dynamic one-dimensional structures.

Authors:  Stefan Hellander
Journal:  J Chem Phys       Date:  2013-07-07       Impact factor: 3.488

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

Authors:  Radek Erban; Hans G Othmer
Journal:  Bull Math Biol       Date:  2014-04       Impact factor: 1.758

5.  Reaction rates for mesoscopic reaction-diffusion kinetics.

Authors:  Stefan Hellander; Andreas Hellander; Linda Petzold
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2015-02-23

6.  Accuracy of the Michaelis-Menten approximation when analysing effects of molecular noise.

Authors:  Michael J Lawson; Linda Petzold; Andreas Hellander
Journal:  J R Soc Interface       Date:  2015-05-06       Impact factor: 4.118

7.  Reaction rates for reaction-diffusion kinetics on unstructured meshes.

Authors:  Stefan Hellander; Linda Petzold
Journal:  J Chem Phys       Date:  2017-02-14       Impact factor: 3.488

8.  Towards a minimal stochastic model for a large class of diffusion-reactions on biological membranes.

Authors:  Michael W Chevalier; Hana El-Samad
Journal:  J Chem Phys       Date:  2012-08-28       Impact factor: 3.488

9.  Perspective: Stochastic algorithms for chemical kinetics.

Authors:  Daniel T Gillespie; Andreas Hellander; Linda R Petzold
Journal:  J Chem Phys       Date:  2013-05-07       Impact factor: 3.488

10.  Intracellular production of hydrogels and synthetic RNA granules by multivalent molecular interactions.

Authors:  Hideki Nakamura; Albert A Lee; Ali Sobhi Afshar; Shigeki Watanabe; Elmer Rho; Shiva Razavi; Allister Suarez; Yu-Chun Lin; Makoto Tanigawa; Brian Huang; Robert DeRose; Diana Bobb; William Hong; Sandra B Gabelli; John Goutsias; Takanari Inoue
Journal:  Nat Mater       Date:  2017-11-06       Impact factor: 43.841

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