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Probabilistic Methods for Bioinformatics

with an Introduction to Bayesian Networks

By: Xia Jiang, Richard E. Neapolitan

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Hardcover | 3 April 2009

At a Glance

Hardcover
424 Pages

Dimensions(cm)
26.04 x 20.32 x 3.18

Hardcover

RRP $126.95

$119.75

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The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. Probabilistic Methods for BioInformatics explains the application of probability and statistics, in particular Bayesian networks, to genetics. This book provides background material on probability, statistics, and genetics, and then moves on to discuss Bayesian networks and applications to bioinformatics.

Rather than getting bogged down in proofs and algorithms, probabilistic methods used for biological information and Bayesian networks are explained in an accessible way using applications and case studies. The many useful applications of Bayesian networks that have been developed in the past 10 years are discussed. Forming a review of all the significant work in the field that will arguably become the most prevalent method in biological data analysis.

Unique coverage of probabilistic reasoning methods applied to bioinformatics data--those methods that are likely to become the standard analysis tools for bioinformatics.
Shares insights about when and why probabilistic methods can and cannot be used effectively;
Complete review of Bayesian networks and probabilistic methods with a practical approach.

Industry Reviews

"Probabilistic Methods for Financial and Marketing Informatics makes important and novel contributions to understanding investment strategies and should be welcomed by practitioners and researchers alike" --Tony Volpon, Strategist/Chief Economist, CM Capital Markets "Richard Neapolitan's new book with Xia Jiang on Bayes nets and its applications to finance and marketing is a must-read for professionals in the finance and marketing communities. The relatively new technique of Bayes nets has great potential for managing uncertainty in all domains. But applications of this technique in finance and marketing have not been widely reported to date. This new book fills this gaping void at a level most professionals can easily understand. Congratulations to Neapolitan and Jiang for this excellent addition to the literature on Bayes nets!" --Prakash P. Shenoy, University of Kansas

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