Bioinformatics: The Machine Learning Approach

Bioinformatics: The Machine Learning Approach

ISBN 0-262-02506-X

Author(s): P.Baldi and S. Brunak

Cloth, 400 pages; August 2001; MIT Press


  1. Introduction
  2. Machine-Learning Foundations: The Probabilistic Framework
  3. Probabilistic Modeling & 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
  11. Stochastic Grammars & Linguistics
  12. Microarrays & Gene Expression
  13. Internet Resources & Public Databases

    A. Statistics
    B. Information Theory, Entropy, & Relative
    C. Probabilistic Graphical Models
    D. HMM Technicalities, Scaling, Periodic
    E. Gaussian Processes, Kernel Methods, and Support Vector Machines
    F. Symbols and Abbreviations
    References Index

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