Description

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.

Computational Molecular Biology: An Introduction

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£85.95

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Usually despatched within 5 days
Paperback / softback by Peter Clote , Rolf Backofen

3 in stock

Short Description:

Recently molecular biology has undergone unprecedented development generating vast quantities of data needing sophisticated computational methods for analysis, processing and... Read more

    Publisher: John Wiley & Sons Inc
    Publication Date: 11/08/2000
    ISBN13: 9780471872528, 978-0471872528
    ISBN10: 0471872520

    Number of Pages: 300

    Non Fiction , Mathematics & Science , Education

    Description

    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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