Literature DB >> 26646867

Model reduction for stochastic chemical systems with abundant species.

Stephen Smith1, Claudia Cianci1, Ramon Grima1.   

Abstract

Biochemical processes typically involve many chemical species, some in abundance and some in low molecule numbers. We first identify the rate constant limits under which the concentrations of a given set of species will tend to infinity (the abundant species) while the concentrations of all other species remains constant (the non-abundant species). Subsequently, we prove that, in this limit, the fluctuations in the molecule numbers of non-abundant species are accurately described by a hybrid stochastic description consisting of a chemical master equation coupled to deterministic rate equations. This is a reduced description when compared to the conventional chemical master equation which describes the fluctuations in both abundant and non-abundant species. We show that the reduced master equation can be solved exactly for a number of biochemical networks involving gene expression and enzyme catalysis, whose conventional chemical master equation description is analytically impenetrable. We use the linear noise approximation to obtain approximate expressions for the difference between the variance of fluctuations in the non-abundant species as predicted by the hybrid approach and by the conventional chemical master equation. Furthermore, we show that surprisingly, irrespective of any separation in the mean molecule numbers of various species, the conventional and hybrid master equations exactly agree for a class of chemical systems.

Year:  2015        PMID: 26646867     DOI: 10.1063/1.4936394

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  5 in total

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Journal:  Biophys J       Date:  2021-10-30       Impact factor: 4.033

2.  A multi-time-scale analysis of chemical reaction networks: II. Stochastic systems.

Authors:  Xingye Kan; Chang Hyeong Lee; Hans G Othmer
Journal:  J Math Biol       Date:  2016-03-05       Impact factor: 2.259

Review 3.  Spatial Stochastic Intracellular Kinetics: A Review of Modelling Approaches.

Authors:  Stephen Smith; Ramon Grima
Journal:  Bull Math Biol       Date:  2018-05-21       Impact factor: 1.758

4.  A Hybrid of the Chemical Master Equation and the Gillespie Algorithm for Efficient Stochastic Simulations of Sub-Networks.

Authors:  Jaroslav Albert
Journal:  PLoS One       Date:  2016-03-01       Impact factor: 3.240

5.  Hybrid CME-ODE method for efficient simulation of the galactose switch in yeast.

Authors:  David M Bianchi; Joseph R Peterson; Tyler M Earnest; Michael J Hallock; Zaida Luthey-Schulten
Journal:  IET Syst Biol       Date:  2018-08       Impact factor: 1.615

  5 in total

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