Bioinformatics the machine learning approach

An unprecedented wealth of data is being generated by genome sequencing projects and other experimental efforts to determine the structure and function of biological molecules. The demands and opportunities for interpreting these data are expanding rapidly. Bioinformatics is the development and appl...

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Bibliographic Details
Main Authors: Baldi, Pierre, Brunak, Søren
Format: eBook Book
Language:English
Published: Cambridge, Massachusetts The MIT Press 2001
MIT Press
A Bradford Book
Edition:2nd edition.
Series:Adaptive computation and machine learning
Subjects:
Bioinformatics
Computer simulation
Machine learning
Markov processes
Mathematical models
Molecular biology
Molecular biology > Computer simulation
Molecular biology > Mathematical models
neural networks (computer science)
ISBN:9780262255707, 0262255707, 026202506X, 9780262025065
Online Access:Get full text
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Table of Contents:
  • Intro -- Contents -- Series Foreword -- Preface -- 1 Introduction -- 2 Machine-Learning Foundations: The Probabilistic Framework -- 3 Probabilistic Modeling and Inference: Examples -- 4 Machine Learning Algorithms -- 5 Neural Networks: The Theory -- 6 Neural Networks: Applications -- 7 Hidden Markov Models: The Theory -- 8 Hidden Markov Models: Applications -- 9 Probabilistic Graphical Models in Bioinformatics -- 10 Probabilistic Models of Evolution: Phylogenetic Trees -- 11 Stochastic Grammars and Linguistics -- 12 Microarrays and Gene Expression -- 13 Internet Resources and Public Databases -- A Statistics -- B Information Theory, Entropy, and Relative Entropy -- C Probabilistic Graphical Models -- D HMM Technicalities, Scaling, Periodic Architectures, State Functions, and Dirichlet Mixtures -- E Gaussian Processes, Kernel Methods, and Support Vector Machines -- F Symbols and Abbreviations -- References -- Index