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Computational Molecular Biology: An Introduction / Edition 1

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Overview

Recently molecular biology has undergone unprecedented development generating vast quantities of data needing sophisticated computational methods for analysis, processing and archiving. This requirement has given birth to the truly interdisciplinary field of computational biology, or bioinformatics, a subject reliant on both theoretical and practical contributions from statistics, mathematics, computer science and biology.

* Provides the background mathematics required to understand why certain algorithms work
* Guides the reader through probability theory, entropy and combinatorial optimization
* In-depth coverage of molecular biology and protein structure prediction
* Includes several less familiar algorithms such as DNA segmentation, quartet puzzling and DNA strand separation prediction
* Includes class tested exercises useful for self-study
* Source code of programs available on a Web site

Primarily aimed at advanced undergraduate and graduate students from bioinformatics, computer science, statistics, mathematics and the biological sciences, this text will also interest researchers from these fields.

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Editorial Reviews

From the Publisher
"...much needed introductory level text on the subject..." (La Doc STI, July 2000)

"...very concise and compact..." (Mathematical Reviews, 2002h)

Booknews
A self-contained introduction for graduate or advanced undergraduate students of biology, computer science, statistics, or mathematics. Clote (computer science and biology, Boston College) and Backofen (U. of Munich) provide the background mathematics required to understand why certain algorithms work. They look at molecular biology, sequence alignment, evolution, hidden Markov models, and structural prediction. The CiP shows the subtitle as A Self-contained Approach to Bioinformatics. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

Table of Contents

Molecular Biology.

Math Primer.

Sequence Alignment.

All About Eve.

Hidden Markov Models.

Structure Prediction.

Appendices.

References.

Index.

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