9780387987859 - Computational Genome Analysis: An Introduction de Deonier, Richard C.; Tavaré, Simon; Waterman, Michael S. (22 résultats)

Hard cover. Sewn binding. Cloth over boards. 535 p. Contains: Unspecified. Statistics for Biology & Health S. Audience: General/trade. Very good. light shelfwear, no ownership marks, almost llike new.

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gebundene Ausgabe. Etat : Gut. 534 Seiten Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber und kann entsprechende Merkmale aufweisen (Rückenschild, Instituts-Stempel.). In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 955.

Gr.-8°, hardcover. Etat : Sehr gut. 2005. 534 Seiten Ausgetragenes Bibliotheksexemplar, Hardcover, Papier in altersgemäßem sehr gutem Zustand. B07-03-03E Sprache: Englisch Gewicht in Gramm: 2133.

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Hardcover. Etat : As New. . . . . 8vo, hardcover. No dj. Fine condition. Covers and contents crisp, clean, unworn, no marking or writing. Binding square and tight. 534 pp. Analysis, Biology, Mathematics, Molecular, 0387987851.

hardcover. Etat : New. In shrink wrap. Looks like an interesting title!

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Etat : New.

Etat : As New. Unread book in perfect condition.

Hardback. Etat : New. 1st ed. 2005. Corr. 3rd printing 2007. Computational Genome Analysis: An Introduction presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book is appropriate for a one-semester course for advanced undergraduate or beginning graduate students, and it can also introduce computational biology to computer scientists, mathematicians, or biologists who are extending their interests into this exciting field.This book features:Topics organized around biological problems, such as sequence alignment and assembly, DNA signals, analysis of gene expression, and human genetic variationPresentation of fundamentals of probability, statistics, and algorithmsImplementation of computational methods with numerous examples based upon the R statistics packageExtensive descriptions and explanations to complement the analytical developmentMore than 100 illustrations and diagrams (some in color) to reinforce concepts and present key results from the primary literatureExercises at the end of chapters.

Etat : New. pp. 572.

Softcover. Etat : sehr gut. Hardcover gr. 8°. xx, 534 pages. with 102 illustrations, including 15 in full color. little rubbed. good condition. Series Statistics for Biology and Health" in englischer Sprache (in english).

Etat : New. pp. 572 Illus.

Etat : New. pp. 572.

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Computational Genome Analysis: An Introduction presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book is appropriate for a one-semester course for advanced undergraduate or beginning graduate students, and it can also introduce computational biology to computer scientists, mathematicians, or biologists who are extending their interests into this exciting field.This book features:- Topics organized around biological problems, such as sequence alignment and assembly, DNA signals, analysis of gene expression, and human genetic variation- Presentation of fundamentals of probability, statistics, and algorithms- Implementation of computational methods with numerous examples based upon the R statistics package- Extensive descriptions and explanations to complement the analytical development- More than 100 illustrations and diagrams (some in color) to reinforce concepts and present key results from the primary literature- Exercises at the end of chaptersFrom the reviews:'The book is useful for its breadth. An impressive variety of topics are surveyed.' Short Book Reviews of the ISI, June 2006'It is a very good book indeed and I would strongly recommend it both to the student hoping to take this study further and to the general reader who wants to know what computational genome analysis is all about.' Mark Bloom for the JRSS, Series A, Volume 169, p. 1006, October 2006'Richard C. Deonier, Simon Tavare and Michael S. Waterman provide us wtih a 'roll up your sleeves and get dirty' (as the authors phrase it in their preface) introduction to the field of computational genome analysis.The bookis carefully written and carefully edited.' Ralf Schmid for Genetic Research, Volume 87, p. 218, 2006.

Hardback. Etat : New. 1st ed. 2005. Corr. 3rd printing 2007. Computational Genome Analysis: An Introduction presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book is appropriate for a one-semester course for advanced undergraduate or beginning graduate students, and it can also introduce computational biology to computer scientists, mathematicians, or biologists who are extending their interests into this exciting field.This book features:Topics organized around biological problems, such as sequence alignment and assembly, DNA signals, analysis of gene expression, and human genetic variationPresentation of fundamentals of probability, statistics, and algorithmsImplementation of computational methods with numerous examples based upon the R statistics packageExtensive descriptions and explanations to complement the analytical developmentMore than 100 illustrations and diagrams (some in color) to reinforce concepts and present key results from the primary literatureExercises at the end of chapters.

Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Computational Genome Analysis: An Introduction presents the foundations of key problems in computational molecular biology and bioinformatics. It focuses on computational and statistical principles applied to genomes, and introduces the mathematics and statistics that are crucial for understanding these applications. The book is appropriate for a one-semester course for advanced undergraduate or beginning graduate students, and it can also introduce computational biology to computer scientists, mathematicians, or biologists who are extending their interests into this exciting field.This book features:- Topics organized around biological problems, such as sequence alignment and assembly, DNA signals, analysis of gene expression, and human genetic variation- Presentation of fundamentals of probability, statistics, and algorithms- Implementation of computational methods with numerous examples based upon the R statistics package- Extensive descriptions and explanations to complement the analytical development- More than 100 illustrations and diagrams (some in color) to reinforce concepts and present key results from the primary literature- Exercises at the end of chaptersFrom the reviews:'The book is useful for its breadth. An impressive variety of topics are surveyed.' Short Book Reviews of the ISI, June 2006'It is a very good book indeed and I would strongly recommend it both to the student hoping to take this study further and to the general reader who wants to know what computational genome analysis is all about.' Mark Bloom for the JRSS, Series A, Volume 169, p. 1006, October 2006'Richard C. Deonier, Simon Tavare and Michael S. Waterman provide us wtih a 'roll up your sleeves and get dirty' (as the authors phrase it in their preface) introduction to the field of computational genome analysis.The bookis carefully written and carefully edited.' Ralf Schmid for Genetic Research, Volume 87, p. 218, 2006 535 pp. Englisch.

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Describes the basic mathematics and statistics underlying computational genomicsFeatures free download of R software statistics packageProvides great crossover material that is interesting and accessible to students in biology, mathematics,.