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. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. Probabilistic Methods for BioInformatics exp...

Full description

Bibliographic Details
Main Author: Neapolitan, Richard E.
Format: eBook
Language:English
Published: Amsterdam Morgan Kaufmann/Elsevier 2009
Subjects:
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
LEADER 03596nmm a2200541 u 4500
001 EB001940422
003 EBX01000000000000001103324
005 00000000000000.0
007 cr|||||||||||||||||||||
008 210123 ||| eng
020 |a 0080919367 
020 |a 9781282168428 
020 |a 9780080919362 
020 |a 9786612168420 
020 |a 6612168420 
020 |a 1282168428 
050 4 |a QH324.2 
100 1 |a Neapolitan, Richard E. 
245 0 0 |a Probabilistic methods for bioinformatics  |b with an introduction to Bayesian networks  |c Richard E. Neapolitan 
260 |a Amsterdam  |b Morgan Kaufmann/Elsevier  |c 2009 
300 |a xii, 406 pages  |b illustrations 
505 0 |a I: Informatics and Baysesian Networks; Introduction to Informatics; Basics of Probability and Statistics; Algorithms for Bayesian Networks; Decision Trees and Influence Diagrams. II Bioinformatics: Background; Applications to Molecular Phylogenetics; Gene Linkage Analysis; Analyzing Gene Expression Data; and more 
505 0 |a Includes bibliographical references (pages 387-399) and index 
653 |a Probabilities / fast 
653 |a Bayesian statistical decision theory / http://id.loc.gov/authorities/subjects/sh85012506 
653 |a Computational Biology 
653 |a Bioinformatics / fast 
653 |a Probability 
653 |a Computational biology / http://id.loc.gov/authorities/subjects/sh2003008355 
653 |a Probabilités 
653 |a Bioinformatics / http://id.loc.gov/authorities/subjects/sh00003585 
653 |a Théorie de la décision bayésienne 
653 |a Bayesian statistical decision theory / fast 
653 |a Computational biology / fast 
653 |a Bio-informatique 
653 |a Probabilities / http://id.loc.gov/authorities/subjects/sh85107090 
653 |a probability / aat 
653 |a COMPUTERS / Bioinformatics / bisacsh 
041 0 7 |a eng  |2 ISO 639-2 
989 |b OREILLY  |a O'Reilly 
776 |z 0080919367 
776 |z 9780123704764 
776 |z 0123704766 
776 |z 9780080919362 
856 4 0 |u https://learning.oreilly.com/library/view/~/9780123704764/?ar  |x Verlag  |3 Volltext 
082 0 |a 519.2 
082 0 |a 572.80285 
520 |a "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."