Stochastic Modelling for Systems Biology (Mathematical and Computational Biology) |  | Author: Darren J. Wilkinson
Publisher: Chapman & Hall/CRC
List Price: $88.95
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Seller: Eric W Blackmon
Rating:  1 reviews
Sales Rank: 758032
Media: Hardcover
Edition: 1
Pages: 280
Number Of Items: 1
Shipping Weight (lbs): 1.2
Dimensions (in): 9.3 x 6.3 x 0.8
ISBN: 1584885408
Dewey Decimal Number: 572.8
EAN: 9781584885405
ASIN: 1584885408
Publication Date: April 18, 2006
Availability: Usually ships in 1-2 business days
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Product Description
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.
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| Customer Reviews:
Correct title: Stochastic modeling of biological systems May 10, 2006
DataGuru (DC)
21 out of 26 found this review helpful
This is one of several recent books with system biology in the title, but first book with emphasis on statistics and stochastic approach. The book discusses some simple math models for biological systems, mostly biochemical models. Main focus is on statistical issues in differentail modeling, those as discussed in the nice Bower and Bolouri (2000) book Computational Modeling of Genetic and Biochemical Networks (Computational Molecular Biology), and the strong point is the use of Bayesian Markov chain Monte Carlo method for stochastic modeling. Weakness is that, the systems considered are too low-dimensional, and there is a long way toward real system biology issues, which will likely be much more complex, and involve potentially many high-dimensional interactions. Overall, it is simply a very straightforward introductory book, lacks depth and breadth. However, it should serve as a good starting point for people who want to learn something about stat and probabilistic methods relevant to bios system modelling.
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