Bioinformatics: The Machine Learning Approach

Topics> 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

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