Isbn: 9781138549289 - stochastic modelling for systems biology, third edition (13 risultati)

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Hardcover. Condizione: Brand New. 3rd new edition. 408 pages. 9.75x6.50x1.00 inches. In Stock.

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Gebunden. Condizione: New. Darren Wilkinson is Professor of Stochastic modelling at Newcastle University in the United Kingdom. He was educated at the nearby University of Durham, where he took his first degree in Mathematics followed by a PhD in Bayesian statisti.

Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Since the first edition of Stochastic Modelling for Systems Biology, there have been many interesting developments in the use of 'likelihood-free' methods of Bayesian inference for complex stochastic models. Having been thoroughly updated to reflect this, this third edition covers everything necessary for a good appreciation of stochastic kinetic modelling of biological networks in the systems biology context. New methods and applications are included in the book, and the use of R for practical illustration of the algorithms has been greatly extended. There is a brand new chapter on spatially extended systems, and the statistical inference chapter has also been extended with new methods, including approximate Bayesian computation (ABC). Stochastic Modelling for Systems Biology, Third Edition is now supplemented by an additional software library, written in Scala, described in a new appendix to the book.New in the Third EditionNew chapter on spatially extended systems, covering the spatial Gillespie algorithm for reaction diffusion master equation models in 1- and 2-d, along with fast approximations based on the spatial chemical Langevin equationSignificantly expanded chapter on inference for stochastic kinetic models from data, covering ABC, including ABC-SMCUpdated R package, including code relating to all of the new materialNew R package for parsing SBML models into simulatable stochastic Petri net modelsNew open-source software library, written in Scala, replicating most of the functionality of the R packages in a fast, compiled, strongly typed, functional languageKeeping with the spirit of earlier editions, all of the new theory is presented in a very informal and intuitive manner, keeping the text as accessible as possible to the widest possible readership. An effective introduction to the area of stochastic modelling in computational systems biology, this new edition adds additional detail and computational methods that will provide a stronger foundation for the development of more advanced courses in stochastic biological modelling. 404 pp. Englisch. …

Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Since the first edition of Stochastic Modelling for Systems Biology, there have been many interesting developments in the use of 'likelihood-free' methods of Bayesian inference for complex stochastic models. Having been thoroughly updated to reflect this, this third edition covers everything necessary for a good appreciation of stochastic kinetic modelling of biological networks in the systems biology context. New methods and applications are included in the book, and the use of R for practical illustration of the algorithms has been greatly extended. There is a brand new chapter on spatially extended systems, and the statistical inference chapter has also been extended with new methods, including approximate Bayesian computation (ABC). Stochastic Modelling for Systems Biology, Third Edition is now supplemented by an additional software library, written in Scala, described in a new appendix to the book.New in the Third EditionNew chapter on spatially extended systems, covering the spatial Gillespie algorithm for reaction diffusion master equation models in 1- and 2-d, along with fast approximations based on the spatial chemical Langevin equationSignificantly expanded chapter on inference for stochastic kinetic models from data, covering ABC, including ABC-SMCUpdated R package, including code relating to all of the new materialNew R package for parsing SBML models into simulatable stochastic Petri net modelsNew open-source software library, written in Scala, replicating most of the functionality of the R packages in a fast, compiled, strongly typed, functional languageKeeping with the spirit of earlier editions, all of the new theory is presented in a very informal and intuitive manner, keeping the text as accessible as possible to the widest possible readership. An effective introduction to the area of stochastic modelling in computational systems biology, this new edition adds additional detail and computational methods that will provide a stronger foundation for the development of more advanced courses in stochastic biological modelling. …