Items related to Statistical Methods in Bioinformatics: An Introduction...
Statistical Methods in Bioinformatics: An Introduction (Statistics for Biology and Health) - Softcover
Synopsis
This book provides an introductory account of probability theory, statistics and stochastic process theory appropriate to computational biology and bioinformatics. These topics are important in the analysis of human genome data.
"synopsis" may belong to another edition of this title.
From the Back Cover
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)
"About this title" may belong to another edition of this title.
Search results for Statistical Methods in Bioinformatics: An Introduction...
Stock Image
Statistical Methods in Bioinformatics: An Introduction (Statistics for Biology and Health)
Seller: BGV Books LLC, Murray, KY, U.S.A.
Seller rating 5 out of 5 stars
Condition: Good. Exact ISBN match. Immediate shipping. No funny business. Seller Inventory # 9781441923028
Quantity: 1 available
Stock Image
Statistical Methods in Bioinformatics: An Introduction
Seller: Anybook.com, Lincoln, United Kingdom
Seller rating 5 out of 5 stars
Condition: 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. Seller Inventory # 9492892
Quantity: 1 available
Seller Image
Statistical Methods in Bioinformatics : An Introduction
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # 11872234-n
Quantity: Over 20 available
Stock Image
Statistical Methods in Bioinformatics: An Introduction (Statistics for Biology and Health)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In. Seller Inventory # ria9781441923028_new
Quantity: Over 20 available
Stock Image
Statistical Methods in Bioinformatics: An Introduction
Published by
Springer-Verlag New York Inc., 2010
ISBN 10: 1441923020
ISBN 13: 9781441923028
New
Paperback / softback
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Paperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 887. Seller Inventory # C9781441923028
Quantity: Over 20 available
Seller Image
Statistical Methods in Bioinformatics
Print on DemandSeller: moluna, Greven, Germany
Seller rating 5 out of 5 stars
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. First book on this subject written from a statistical viewpointIncludes methods important in the analysis of human genome dataOnly basic knowledge of biology is assumedAdvances in computers and biotechnology have had a profound i. Seller Inventory # 4172828
Quantity: Over 20 available
Seller Image
Statistical Methods in Bioinformatics
Published by
Springer New York Nov 2010, 2010
ISBN 10: 1441923020
ISBN 13: 9781441923028
New
Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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) 620 pp. Englisch. Seller Inventory # 9781441923028
Quantity: 2 available
Seller Image
Statistical Methods in Bioinformatics : An Introduction
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # 11872234-n
Quantity: Over 20 available
Seller Image
Statistical Methods in Bioinformatics : An Introduction
Published by
Springer New York, Springer New York, 2010
ISBN 10: 1441923020
ISBN 13: 9781441923028
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: 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). Seller Inventory # 9781441923028
Quantity: 1 available
Seller Image
Statistical Methods in Bioinformatics
Published by
Springer New York, Springer New York Nov 2010, 2010
ISBN 10: 1441923020
ISBN 13: 9781441923028
New
Taschenbuch
First Edition
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Neuware -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)Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 620 pp. Englisch. Seller Inventory # 9781441923028
Quantity: 2 available