Stochastic Modelling for Systems Biology

Darren J. Wilkinson - Collection Mathematical and Computational Biology Series

280 pages, parution le 03/05/2006

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Résumé

Although stochastic kinetic models are increasingly accepted as the best way to represent and simulate genetic and biochemical networks, most researchers in the field have limited knowledge of stochastic process theory. The stochastic processes formalism provides a beautiful, elegant, and coherent foundation for chemical kinetics and there is a wealth of associated theory every bit as powerful and elegant as that for conventional continuous deterministic models. The time is right for an introductory text written from this perspective.

Stochastic Modelling for Systems Biology presents an accessible introduction to stochastic modelling using examples that are familiar to systems biology researchers. Focusing on computer simulation, the author examines the use of stochastic processes for modelling biological systems. He provides a comprehensive understanding of stochastic kinetic modelling of biological networks in the systems biology context. The text covers the latest simulation techniques and research material, such as parameter inference, and includes many examples and figures as well as software code in R for various applications.

While emphasizing the necessary probabilistic and stochastic methods, the author takes a practical approach, rooting his theoretical development in discussions of the intended application. Written with self-study in mind, the book includes technical chapters that deal with the difficult problems of inference for stochastic kinetic models from experimental data. Providing enough background information to make the subject accessible to the non-specialist, the book integrates a fairly diverse literature into a single convenient and notationally consistent source.

Sommaire

Introduction to biological modelling
Representation of biochemical networks
Probability models
Stochastic simulation
Markov processes
Chemical and biochemical kinetics
Case studies
Beyond the Gillespie algorithm
Bayesian inference and MCMC
Inference for stochastic kinetic models
Conclusions
SBML models

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Chapman and Hall / CRC
Auteur(s)	Darren J. Wilkinson
Collection	Mathematical and Computational Biology Series
Parution	03/05/2006
Nb. de pages	280
Format	16 x 24
Couverture	Relié
Poids	525g
Intérieur	Noir et Blanc
EAN13	9781584885405
ISBN13	978-1-58488-540-5