Book contents
- Frontmatter
- Contents
- Preface
- 1 Stochastic Simulation of Chemical Reactions
- 2 Deterministic versus Stochastic Modelling
- 3 Stochastic Differential Equations
- 4 Diffusion
- 5 Efficient Stochastic Modelling of Chemical Reactions
- 6 Stochastic Reaction–Diffusion Models
- 7 SSAs for Reaction–Diffusion–Advection Processes
- 8 Microscopic Models of Brownian Motion
- 9 Multiscale and Multi-Resolution Methods
- Appendix
- References
- Index
1 - Stochastic Simulation of Chemical Reactions
Published online by Cambridge University Press: 04 November 2019
- Frontmatter
- Contents
- Preface
- 1 Stochastic Simulation of Chemical Reactions
- 2 Deterministic versus Stochastic Modelling
- 3 Stochastic Differential Equations
- 4 Diffusion
- 5 Efficient Stochastic Modelling of Chemical Reactions
- 6 Stochastic Reaction–Diffusion Models
- 7 SSAs for Reaction–Diffusion–Advection Processes
- 8 Microscopic Models of Brownian Motion
- 9 Multiscale and Multi-Resolution Methods
- Appendix
- References
- Index
Summary
This chapter provides an introduction to stochastic methods for modelling spatially homogeneous systems of chemical reactions. The Gillespie stochastic simulation algorithm and the chemical master equation are presented using simple examples of chemical systems. The chemical master equation is analysed for chemical systems containing zeroth-order, first-order and second-order chemical reactions. For zeroth-order and first-order chemical reactions, the average behaviour of the stochastic chemical system is described by the ordinary differential equations (ODEs) given by the standard deterministic model. However, when we consider higher-order chemical reactions, for which the deterministic description is nonlinear, the deterministic ODE model does not provide an exact description of the average behaviour of the stochastic system.
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- Information
- Stochastic Modelling of Reaction–Diffusion Processes , pp. 1 - 32Publisher: Cambridge University PressPrint publication year: 2020