Stochastic modelling for systems biology

✍ Scribed by Wilkinson, Darren James

• Publisher: CRC Press/Taylor & Francis Group
• Year: 2012
• Tongue: English
• Leaves: 360
• Series: Chapman & Hall/CRC mathematical and computational biology series (Unnumbered)
• Edition: Second edition
• Category: Library

✦ Synopsis

"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. Re-written to reflect this modern perspective, this second edition covers everything necessary for a good appreciation of stochastic kinetic modelling of biological networks in the systems biology context. Keeping with the spirit of the first edition, 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"--Provided by publisher. Read more...

Abstract: "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. Re-written to reflect this modern perspective, this second edition covers everything necessary for a good appreciation of stochastic kinetic modelling of biological networks in the systems biology context. Keeping with the spirit of the first edition, 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"--Provided by publisher

✦ Table of Contents

Content: I. Modelling and networks. Introduction to biological modelling --
Representation of biochemical networks --
II. Stochastic processes and simulation. Probability models --
Stochastic simulation --
Markov processes --
III. Stochastic chemical kinetics. Chemical and biochemical kinetics --
Case studies --
Beyond the Gillespie algorithm --
IV. Bayesian inference. Bayesian inference and MCMC --
Inference for stochastic kinetic models --
Conclusions.

✦ Subjects

Biological systems -- Mathematical models. Systems biology. Systems Biology -- methods. Kinetics. Models, Biological. Models, Statistical. Stochastic Processes. SCIENCE -- Life Sciences -- Molecular Biology.