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Computational Molecular Biology: An Introduction: 2 (Wiley Series in Mathematical & Computational Biology) - Tapa blanda

Clote, Clote

 
9780471872528: Computational Molecular Biology: An Introduction: 2 (Wiley Series in Mathematical & Computational Biology)

Sinopsis

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del autor

Peter Clote is the author of Computational Molecular Biology: An Introduction, published by Wiley.

Rolf Backofen is the author of Computational Molecular Biology: An Introduction, published by Wiley.

De la contraportada

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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