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
2 - Deterministic versus Stochastic Modelling
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 presents examples of chemical systems where deterministic modelling fails and a stochastic approach is necessary. They include a chemical system with stochastic switching between favourable states of a system, and systems close to the bifurcation points of the corresponding deterministic ordinary differential equation (ODE) models. It is shown that the stochastic model might have qualitatively different properties than its deterministic counterpart for some parameter regimes. A chemical reaction system can also be redesigned, by adding extra reactions, in such a way that its stochastic behaviour qualitatively changes, while its deterministic ODEs do not change at all. In particular, there exist many stochastic reaction networks that correspond to the same deterministic ODE model.
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- Stochastic Modelling of Reaction–Diffusion Processes , pp. 33 - 58Publisher: Cambridge University PressPrint publication year: 2020