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Bioinformatics

Sequence and Genome Analysis

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The application of computational methods to DNA and protein science is an exciting development in biology. Bioinformatics: Sequence and Genome Analysis is a comprehensive introduction to this emerging field of study. The book has many valuable features. It is written for biologists who want to understand methods of sequence and structure analysis and how the necessary computer programs work. Sequence alignment, structure prediction, phylogenetic and gene prediction, database searching, and genome analysis are clearly explained and illustrated. Underlying algorithms and assumptions are also explained for the non-specialist, and examples are presented in simple numerical terms rather than complex formulas and notation. Theoretical underpinnings are linked to biological problems and their solutions, while extensive tables provide descriptions and Web sources for a broad range of publicly available software. Based on the author's experience as a molecular geneticist and bioinformaticist at the University of Arizona, this is an educational book, useful as a laboratory reference for investigators and also as a teaching reference for graduate and undergraduate students.

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Bioinformatics, David W. Mount

Language
Released
2001
Binding
(Paperback),
Book condition
Damaged
Price
€12.49

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Title
Bioinformatics
Subtitle
Sequence and Genome Analysis
Language
English
Format
Paperback
Pages
564
ISBN10
0879696087
ISBN13
9780879696085
Series
Description
The application of computational methods to DNA and protein science is an exciting development in biology. Bioinformatics: Sequence and Genome Analysis is a comprehensive introduction to this emerging field of study. The book has many valuable features. It is written for biologists who want to understand methods of sequence and structure analysis and how the necessary computer programs work. Sequence alignment, structure prediction, phylogenetic and gene prediction, database searching, and genome analysis are clearly explained and illustrated. Underlying algorithms and assumptions are also explained for the non-specialist, and examples are presented in simple numerical terms rather than complex formulas and notation. Theoretical underpinnings are linked to biological problems and their solutions, while extensive tables provide descriptions and Web sources for a broad range of publicly available software. Based on the author's experience as a molecular geneticist and bioinformaticist at the University of Arizona, this is an educational book, useful as a laboratory reference for investigators and also as a teaching reference for graduate and undergraduate students.