Stochastic Modelling of Reaction–Diffusion Processes: 60 (Cambridge Texts in Applied Mathematics, Series Number 60) - Tapa blanda

Libro 41 de 44: Cambridge Texts in Applied Mathematics

Erban, Radek; Chapman, S. Jonathan

 
9781108703000: Stochastic Modelling of Reaction–Diffusion Processes: 60 (Cambridge Texts in Applied Mathematics, Series Number 60)

Sinopsis

This practical introduction to stochastic reaction-diffusion modelling is based on courses taught at the University of Oxford. The authors discuss the essence of mathematical methods which appear (under different names) in a number of interdisciplinary scientific fields bridging mathematics and computations with biology and chemistry. The book can be used both for self-study and as a supporting text for advanced undergraduate or beginning graduate-level courses in applied mathematics. New mathematical approaches are explained using simple examples of biological models, which range in size from simulations of small biomolecules to groups of animals. The book starts with stochastic modelling of chemical reactions, introducing stochastic simulation algorithms and mathematical methods for analysis of stochastic models. Different stochastic spatio-temporal models are then studied, including models of diffusion and stochastic reaction-diffusion modelling. The methods covered include molecular dynamics, Brownian dynamics, velocity jump processes and compartment-based (lattice-based) models.

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Acerca de los autores

Radek Erban is Professor of Mathematics at the University of Oxford, a Fellow of Merton College, Oxford and a Royal Society University Research Fellow.

S. Jonathan Chapman is Professor of Mathematics and its Applications at the University of Oxford, and a Fellow of Mansfield College, Oxford.

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Otras ediciones populares con el mismo título

9781108498128: Stochastic Modelling of Reaction-Diffusion Processes: 60 (Cambridge Texts in Applied Mathematics, Series Number 60)

Edición Destacada

ISBN 10:  1108498124 ISBN 13:  9781108498128
Editorial: Cambridge University Press, 2020
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