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 m

part I|2 pages

I Modelling and networks

chapter 1|18 pages

Introduction to biological modelling

chapter 2|28 pages

Representation of biochemical networks

part II|2 pages

Stochastic processes and simulation

chapter 3|48 pages

Probability models

chapter 4|24 pages

Stochastic simulation

chapter 5|46 pages

Markov processes

part III|2 pages

III Stochastic chemical kinetics

chapter 6|32 pages

Chemical and biochemical kinetics

chapter 7|18 pages

Case studies

chapter 8|26 pages

Beyond the Gillespie algorithm

part IV|2 pages

IV Bayesian inference

chapter 9|28 pages

Bayesian inference and MCMC

chapter 10|34 pages

Inference for stochastic kinetic models

chapter 11|4 pages

Conclusions