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Idioma: Inglés
Publicado por Springer, New York, NY, 2005
ISBN 10: 0387987851 ISBN 13: 9780387987859
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Añadir al carritoHard 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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Añadir al carritogebundene 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.
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Añadir al carritoGr.-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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Añadir al carritoHardcover. Condición: 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.
Idioma: Inglés
Publicado por Springer-Verlag New York Inc., New York, NY, 2010
ISBN 10: 1441931627 ISBN 13: 9781441931627
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Añadir al carritoPaperback. Condición: new. Paperback. 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 book is carefully written and carefully edited." Ralf Schmid for Genetic Research, Volume 87, p. 218, 2006 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 to understand these applications. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Añadir al carritoCondición: New. pp. 572.
Idioma: Inglés
Publicado por Springer-Verlag New York Inc., US, 2005
ISBN 10: 0387987851 ISBN 13: 9780387987859
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
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Añadir al carritoHardback. Condición: 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.
Publicado por Springer, New Delhi, 2008
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Añadir al carritoPaperback. 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.
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Añadir al carritoCondición: New. pp. 572 Illus.
Idioma: Inglés
Publicado por New York. Springer. 2005., 2005
ISBN 10: 0387987851 ISBN 13: 9780387987859
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Añadir al carritoSoftcover. 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).
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Añadir al carritoTaschenbuch. Condición: Neu. Computational Genome Analysis | An Introduction | Richard C. Deonier (u. a.) | Taschenbuch | xx | Englisch | 2010 | Springer | EAN 9781441931627 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Añadir al carritoCondición: New. pp. 572.
Idioma: Inglés
Publicado por Springer New York, Springer New York, 2010
ISBN 10: 1441931627 ISBN 13: 9781441931627
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Añadir al carritoTaschenbuch. Condición: 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.
Idioma: Inglés
Publicado por Springer-Verlag New York Inc., New York, NY, 2010
ISBN 10: 1441931627 ISBN 13: 9781441931627
Librería: AussieBookSeller, Truganina, VIC, Australia
Original o primera edición
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Añadir al carritoPaperback. Condición: new. Paperback. 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 book is carefully written and carefully edited." Ralf Schmid for Genetic Research, Volume 87, p. 218, 2006 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 to understand these applications. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Añadir al carritoBuch. Condición: 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.
Idioma: Inglés
Publicado por Springer-Verlag New York Inc., US, 2005
ISBN 10: 0387987851 ISBN 13: 9780387987859
Librería: Rarewaves.com UK, London, Reino Unido
EUR 121,74
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Añadir al carritoHardback. Condición: 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.