'Delete states' diaporamas de présentation

Hidden Markov Models

Hidden Markov Models. Probabilistic model of a Multiple sequence alignment. No indel penalties are needed Experimentally derived information can be incorporated Parameters are adjusted to represent observed variation. Requires at least 20 sequences. The Evolution of a Sequence.

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Summary of Chapter 7:

Hidden Markov Models Supplement to the Probabilistic Graphical Models Course 2009 School of Computer Science and Engineering Seoul National University. Summary of Chapter 7: P. Baldi and S. Brunak, Bioinformatics: The Machine Learning Approach, MIT Press, 1998. Outline. Introduction

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Profile Hidden Markov Models

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