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Monday, 6 May 2013

Probabilistic Methods for Bioinformatics

Posted on 03:23 by Unknown
Probabilistic Methods for Bioinformatics
Author: Richard E. Neapolitan
Edition: 1
Binding: Hardcover
ISBN: 0123704766
Publisher: Morgan Kaufmann

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Probabilistic Methods for Bioinformatics: with an Introduction to Bayesian Networks



The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions.
Probabilistic Methods for Bioinformatics: With and Introduction to Bayesian Networks, ISBN-13: 9780123704764, ISBN-10: 0123704766
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

Essential Bioinformatics


Essential Bioinformatics is a concise yet comprehensive textbook of bioinformatics, which provides a broad introduction to the entire field. Written specifically for a life science audience, the basic

Pattern Recognition and Machine Learning (Information Science and Statistics)


This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact a

Applied Statistics for Network Biology (Quantitative and Network Biology (VCH))


The book introduces to the reader a number of cutting edge statistical methods which can e used for the analysis of genomic, proteomic and metabolomic data sets. In particular in the field of systems

Artificial Intelligence: A Modern Approach (3rd Edition)


Artificial Intelligence: A Modern Approach, 3e offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textb

Learning Bayesian Networks


In this first edition book, methods are discussed for doing inference in Bayesian networks and inference diagrams. Hundreds of examples and problems allow readers to grasp the information. <

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