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Comparative gene finding : models, algorithms, and implementation / Marina Axelson-Fisk.

By: Axelson-Fisk, MarinaMaterial type: TextTextSeries: Computational biology: Publisher: London ; New York : Springer, c2010Description: xv, 304 p. : ill. ; 25 cmISBN: 9781849961035 (hbk. : alk. paper); 1849961034 (hbk. : alk. paper); 9781849961042 (eISBN); 1849961042 (ebk.)Subject(s): Genomics -- Data processing | Computational Biology | Chromosome Mapping | Genomics -- methodsDDC classification: 574.880258 LOC classification: QH447 | .A94 2010Summary: "Comparative genomics is an emerging field, which is being fed by an explosion in the number of possible biological sequences. This has led to an immense demand for faster, more efficient and more robust computer algorithms to analyze this large amount of data." "This unique text/reference describes the state of the art in computational gene finding, with a particular focus on comparative approaches. Providing both an overview of the various methods that are applied in the field, and a concise guide on how computational gene finders are built, the book covers a broad range of topics from probability theory, statistics, information theory, optimization theory and numerical analysis. The text assumes the reader has some background in bioinformatics, especially in mathematics and mathematical statistics. A basic knowledge of analysis, probability theory and random processes would also aid the reader." --Book Jacket.
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574.880285 AXE (Browse shelf) Not for loan (Restricted Access) 135427

Includes bibliographical references and index.

"Comparative genomics is an emerging field, which is being fed by an explosion in the number of possible biological sequences. This has led to an immense demand for faster, more efficient and more robust computer algorithms to analyze this large amount of data." "This unique text/reference describes the state of the art in computational gene finding, with a particular focus on comparative approaches. Providing both an overview of the various methods that are applied in the field, and a concise guide on how computational gene finders are built, the book covers a broad range of topics from probability theory, statistics, information theory, optimization theory and numerical analysis. The text assumes the reader has some background in bioinformatics, especially in mathematics and mathematical statistics. A basic knowledge of analysis, probability theory and random processes would also aid the reader." --Book Jacket.

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