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Hidden Markov Models of Bioinformatics (Computational Biology)
by Timo Koski
Binding: Paperback, 1 edition, 416 pages
Publisher: Springer
Weight: 1.37 pound
Dimension: H: 0.94 x L: 9.13 x W: 6.14 inches
ISBN 10: 1402001363
ISBN 13: 9781402001369
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Book Description:
The purpose of this book is to give a thorough and systematic introduction to probabilistic modeling in bioinformatics. The book contains a mathematically strict and extensive presentation of the kind of probabilistic models that have turned out to be useful in genome analysis. Questions of parametric inference, selection between model families, and various architectures are treated. Several examples are given of known architectures (e.g., profile HMM) used in genome analysis. Audience: This book will be of interest to advanced undergraduate and graduate students with a fairly limited background in probability theory, but otherwise well trained in mathematics and already familiar with at least some of the techniques of algorithmic sequence analysis.

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