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Probabilistic Methods for Bioinformatics
with an Introduction to Bayesian Networks
Learn about Bioinformatics, practically, with the use of probabilistic methods!
Richard E. Neapolitan (Author)
9780123704764
Hardback, published 12 May 2009
424 pages
23.4 x 19 x 2.7 cm, 0.89 kg
"This book provides background material on probability, statistics, and genetics, and then moves on to discuss Bayesian networks and applications to bioinformatics…probabilistic methods used for biological information and Bayesian networks are explained in an accessible way using applications and case studies." --Zentralblatt MATH 1284-1
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.
I: Background Chapter 1: Probabilistic Informatics Chapter 2: Probability Basics Chapter 3: Statistics Basics Chapter 4: Genetics Basics II: Bayesian Networks Chapter 5: Foundations of Bayesian Networks Chapter 6: Further Properties of Bayesian Networks Chapter 7: Learning Bayesian Network Parameters Chapter 8: Learning Bayesian Network Structure III: Bioinformatics Applications Chapter 9: Nonmolecular Evolutionary Genetics Chapter 10: Molecular Evolutionary Genetics Chapter 11: Molecular Phylogenetics Chapter 12: Analyzing Gene Expression Data Chapter 13: Genetic Linkage Analysis Bibliography Index
Subject Areas: Probability & statistics [PBT], Medical bioinformatics [MBF]
