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The Bioinformatics : Machine Learning Approach.
A guide to machine learning approaches and their application to the analysis of biological data.
| Call Number: | Libro Electrónico |
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| Main Author: | |
| Format: | Electronic eBook |
| Language: | Inglés |
| Published: |
MIT Press
2001.
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| Series: | Adaptive computation and machine learning Bioinformatics
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| Subjects: | |
| Online Access: | Texto completo |
Table of 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 EntropyC 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.