Deonier richard (33 resultados)

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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.

gebundene Ausgabe. Condición: 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. Condición: 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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Softcover. Condición: 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).

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

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Condición: New. pp. xx + 535.

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Condición: New.

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Paperback. Condición: As New. Reprint. International edition Contents Acknowledgements. 1. Biology in a nutshell. 2. Words. 3. Word distributions and occurrences. 4. Physical mapping of DNA. 5. Genome rearrangements. 6. Sequence alignment. 7. Rapid Alignment Methods FASTA and BLAST. 8. DNA Sequence Assembly. 9. Signals in DNA. 10. Similarity distance and clustering. 11. Measuring expression of genome information. 12. Inferring the past phylogenetic trees. 13. Genetic variation in populations. 14. Comparative genomics. Glossary 1. A brief introduction to R. 2. Internet bioinformatics resources. 3. Miscellaneous data. 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. This book is appropriate for a one semester course for advanced 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 (15 in color) to reinforce concepts and present key results from the primary literature. Exercises at the end of chapters. 534 pp.…

Hardback. Condición: New. 1st ed. 2005. Corr. 3rd printing 2007. This book 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 features a free download of the R software statistics package and the text provides great crossover material that is interesting and accessible to students in biology, mathematics, statistics and computer science. More than 100 illustrations and diagrams reinforce concepts and present key results from the primary literature. Exercises are given at the end of chapters. 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.…

Condición: New. pp. 572.

Hardback. Condición: New. 1st ed. 2005. Corr. 3rd printing 2007. This book 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 features a free download of the R software statistics package and the text provides great crossover material that is interesting and accessible to students in biology, mathematics, statistics and computer science. More than 100 illustrations and diagrams reinforce concepts and present key results from the primary literature. Exercises are given at the end of chapters. 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.…

Condición: new. Questo è un articolo print on demand.

PF. Condición: New. This item is printed on demand. Brand new book, sourced directly from publisher. Dispatch time is 6-7 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Taschenbuch. Condición: 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 572 pp. Englisch.…

Paperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Condición: 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..…

Buch. Condición: 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.…

Condición: New. Print on Demand pp. xx + 535 117 Illus. (15 Col.).

Condición: New. PRINT ON DEMAND pp. xx + 535.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book 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 features a free download of the R software statistics package and the text provides great crossover material that is interesting and accessible to students in biology, mathematics, statistics and computer science. More than 100 illustrations and diagrams reinforce concepts and present key results from the primary literature. Exercises are given at the end of chapters. 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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 572 pp. Englisch.…