statistical methods bioinformatics introduction (39 resultados)

Hardcover. Condición: Très bon. Ancien livre de bibliothèque. Légères traces d'usure sur la couverture. Edition 2001. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Slight signs of wear on the cover. Edition 2001. Ammareal gives back up to 15% of this item's net price to charity organizations.

Condición: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,900grams, ISBN:9780387952291.

Condición: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,900grams, ISBN:9780387952291.

Condición: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,900grams, ISBN:9780387952291.

Condición: Good. Used book that is in clean, average condition without any missing pages.

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Condición: acceptable. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in Acceptable condition! Any other included accessories are also in Acceptable condition showing use. Use can include some highlighting and writing, page and cover creases as well as other types visible wear such as cover tears discoloration, staining, marks, scuffs, etc. All pages intact.

Condición: good. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in Good condition! Any other included accessories are also in Good condition showing use. Use can include some highlighting and writing, page and cover creases as well as other types visible wear.

Condición: good. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in Good condition! Any other included accessories are also in Good condition showing use. Use can include some highlighting and writing, page and cover creases as well as other types visible wear.

8° , Hardcover/Pappeinband. XX / 597 S. Einband mit leichten Gebrauchsspuren, gut erhaltenes Bibliotheksexemplar (Stempel), with 30 figures Sprache: Deutsch Gewicht in Gramm: 550.

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hardcover. Condición: Good. 2nd. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

Condición: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1050grams, ISBN:9781441923028.

Condición: New. In.

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Paperback. Condición: new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.

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Condición: New.

Condición: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

Condición: New.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community.This book provides an introduction to some of these new methods.The main biological topics treated include sequence analysis, BLAST, microarray analysis, gene finding, and the analysis of evolutionary processes.The main statistical techniques covered include hypothesis testing and estimation, Poisson processes, Markov models and Hidden Markov models, and multiple testing methods.The second edition features new chapters on microarray analysis and on statistical inference, including a discussion of ANOVA, and discussions of the statistical theory of motifs and methods based on the hypergeometric distribution. Much material has been clarified and reorganized.The book is written so as to appeal to biologists and computer scientists who wish to know more about the statistical methods of the field, as well as to trained statisticians who wish to become involved with bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, but with an emphasis on material relevant to later chapters and often not covered in standard introductory texts. Later chapters should be immediately accessible to the trained statistician. Sufficient mathematical background consists of introductory courses in calculus and linear algebra. The basic biological concepts that are used are explained, or can be understood from the context, and standard mathematical concepts are summarized in an Appendix. Problems are provided at the end of each chapter allowing the reader to develop aspects of the theory outlined in the main text. Warren J. Ewens holds the Christopher H. Brown Distinguished Professorship at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics. He is a senior editor of Annals of Human Genetics and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceedings of the Royal Society B and SIAM Journal in Mathematical Biology. He is a fellow of the Royal Society and the Australian Academy of Science.Gregory R. Grant is a senior bioinformatics researcher in the University of Pennsylvania Computational Biology and Informatics Laboratory. He obtained his Ph.D. in number theory from the University of Maryland in 1995 and his Masters in Computer Science from the University of Pennsylvania in 1999.Comments on the first edition:'This book would be an ideal text for a postgraduate course.[and] is equally well suited to individual study. I would recommend the book highly.' (Biometrics) 'Ewens and Grant have given us a very welcome introduction to what is behind those pretty [graphical user] interfaces.' (Naturwissenschaften) 'The authors do an excellent job of presenting the essence of the material without getting bogged down in mathematical details.' (Journal American Statistical Association) 'The authors have restructured classical material to a great extent and the new organization of the different topics is one of the outstanding services of the book.' (Metrika).

Condición: New. In.

Condición: New.

Condición: New.

Paperback. Condición: Brand New. 2nd ed. 2005. corr. 2nd printing edition. 608 pages. 8.90x6.00x1.60 inches. In Stock.

Condición: New.

Condición: New.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Advances in computers and biotechnology have had a profound impact on biomedical research, and as a result complex data sets can now be generated to address extremely complex biological questions. Correspondingly, advances in the statistical methods necessary to analyze such data are following closely behind the advances in data generation methods. The statistical methods required by bioinformatics present many new and difficult problems for the research community.This book provides an introduction to some of these new methods.The main biological topics treated include sequence analysis, BLAST, microarray analysis, gene finding, and the analysis of evolutionary processes.The main statistical techniques covered include hypothesis testing and estimation, Poisson processes, Markov models and Hidden Markov models, and multiple testing methods.The second edition features new chapters on microarray analysis and on statistical inference, including a discussion of ANOVA, and discussions of the statistical theory of motifs and methods based on the hypergeometric distribution. Much material has been clarified and reorganized.The book is written so as to appeal to biologists and computer scientists who wish to know more about the statistical methods of the field, as well as to trained statisticians who wish to become involved with bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, but with an emphasis on material relevant to later chapters and often not covered in standard introductory texts. Later chapters should be immediately accessible to the trained statistician. Sufficient mathematical background consists of introductory courses in calculus and linear algebra. The basic biological concepts that are used are explained, or can be understood from the context, and standard mathematical concepts are summarized in an Appendix. Problems are provided at the end of each chapter allowing the reader to develop aspects of the theory outlined in the main text. Warren J. Ewens holds the Christopher H. Brown Distinguished Professorship at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics. He is a senior editor of Annals of Human Genetics and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceedings of the Royal Society B and SIAM Journal in Mathematical Biology. He is a fellow of the Royal Society and the Australian Academy of Science.Gregory R. Grant is a senior bioinformatics researcher in the University of Pennsylvania Computational Biology and Informatics Laboratory. He obtained his Ph.D. in number theory from the University of Maryland in 1995 and his Masters in Computer Science from the University of Pennsylvania in 1999.Comments on the first edition:'This book would be an ideal text for a postgraduate course.[and] is equally well suited to individual study. I would recommend the book highly.' (Biometrics) 'Ewens and Grant have given us a very welcome introduction to what is behind those pretty [graphical user] interfaces.' (Naturwissenschaften) 'The authors do an excellent job of presenting the essence of the material without getting bogged down in mathematical details.' (Journal American Statistical Association) 'The authors have restructured classical material to a great extent and the new organization of the different topics is one of the outstanding services of the book.' (Metrika).