Stochastic Modelling for Systems Biology, Third Edition, 3rd Edition, 9781138549289
Hardcover
Since its first edition, 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 kin…

Stochastic Modelling for Systems Biology, Third Edition, 3rd Edition

$327.95

  • Hardcover

    384 pages

  • Release Date

    21 November 2018

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Summary

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 prac…

Book Details

ISBN-13:9781138549289
ISBN-10:1138549282
Author:Darren J. Wilkinson
Publisher:Taylor & Francis Ltd
Imprint:CRC Press
Format:Hardcover
Number of Pages:384
Edition:3rd
Release Date:21 November 2018
Weight:720g
Dimensions:234mm x 156mm
Series:Chapman & Hall/CRC Computational Biology Series
What They're Saying

Critics Review

”…stochastic modeling has drawn the attention of many researchers in biology and physiology. A textbook, with much elaboration, is highly valuable to understanding the underlying mathematical and computational methods in biological stochastic modeling. Prof Wilkinson has designed the content of this book to fill a gap in the educational text/reference books available for students/researchers learning about stochastic modeling in biological systems… This third edition book almost covers all of the material necessary for students studying stochastic kinetics modelling. The exercises in every chapter certainly illustrate the theory and concept of the book. Appendices A and B elaborate on all of the SBML code and other software associated with the book. The codes are also complemented by links to the author’s webpage and a GitHub repository. The author must be appreciated for adding so many references for further reading. The content of the book is designed for a one-semester graduate-level course in stochastic modeling in biology. Thus, this book is targeted at master and graduate students in interdisciplinary subjects such as applied mathematics, computational biology, bioinformatics, biophysics, Biochemistry, and biomedical engineering.”- Chitaranjan Mahapatra, Appeared in ISCB News, January 2020

About The Author

Darren J. Wilkinson

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 statistics which he completed in 1995. He moved to a Lectureship in Statistics at Newcastle University in 1996, where he has remained since, being promoted to his current post in 2007. Professor Wilkinson is interested in computational statistics and Bayesian inference and in the application of modern statistical technology to problems in statistical bioinformatics and systems biology. He is also interested in some of the “big data” challenges that arise in bioscience and more generally. He serves on Biotechnology and Biological Sciences Research Council’s Strategy Advisory Panel for Exploiting new ways of working and is co-Director of Newcastle’s Engineering and Physical Sciences Research Council Centre for Doctoral Training in Cloud Computing for Big Data. He is also a Fellow of the Alan Turing Institute for data science and artificial intelligence.

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