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Statistical Methods in Bioinformatics
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Statistical Methods in Bioinformatics

Statistical Methods in Bioinformatics

An Intrtoduction

Warren J. Ewens, Ewens, Gregory R. Grant

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476 pages, parution le 01/05/2001
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Résumé

Advances in computers and biotechnology have had an immense impact on the biomedical fields, with broad consequences for humanity. Correspondingly, new areas of probability and statistics are being developed specifically to meet the needs of this area. There is now a necessity for a text that introduces probability and statistics in the bioinformatics context. This book also describes some of the main statistical applications in the field, including BLAST, gene finding, and evolutionary inference, much of which has not yet been summarized in an introductory textbook format. This book grew out of a need to teach bioinformatics to graduate students at the University of Pennsylvania. At the same time however, it is organized to appeal to a wider audience. In particular it should appeal to any biologist or computer scientist who wants to know more about the statistical methods of the field, as well as to a trained statistician who wishes to become involved in bioinformatics. The earlier chapters introduce the concepts of probability and statistics at an elementary level, and will be accessible to students who have only had introductory calculus and linear algebra. Later chapters are immediately accessible to the trained statistician. Only a basic understanding of biological concepts is assumed, and all concepts are explained when used or can be understood from the context. Several chapters contain material independent of that in other chapters, so that the reader interested in certain areas can proceed directly to those areas. Warren Ewens is Professor of Biology at the University of Pennsylvania. He is the author of two books, Population Genetics and Mathematical Population Genetics, and has served on the editorial boards of Theoretical Population Biology, GENETICS, Proceeding of the Royal Society B and SIAM Journal in Mathematical Biology. He was recently awarded the Gold Medal of the Australian Statistical Society and elected as Fellow of the Royal Society. His research interests are in evolutionary population genetics, linkage analysis for human diseases, and bioinformatics. Gregory Grant is a bioinformatics researcher at the University of Pennsylvania in the Computational Biology and Informatics Laboratory (CBIL), where he has been since 1998. In 1995 he received a Ph.D. in Mathematics from the University of Maryland and in 1999 a Masters in Computer Science from the University of Pennsylvania. His research interests are in bioinformatics in general and in particular in the statistical analysis of gene expression data and significance testing methods for IBD-mapping.

Contents

  • An Introduction to Probability Theory: One Random Variable
  • An Introduction to Probability Theory: Many Random Variables
  • Statistics: An Introduction to Statistical Inference
  • Stochastic Processes: An Introduction to Poisson Processes and Markov Chains
  • The Analysis of DNA Sequence Patterns: One sequence
  • The Analysis of DNA Sequences: Multiple sequences
  • Stochastic Processes: Random Walks
  • Statistics: Classical Estimation and Hypothesis Testing
  • BLAST
  • Stochastic Processes: Markov Chains
  • Hidden Markov Models
  • Computationally intensive methods
  • Evolutionary models
  • Phylogenetica tree estimation

L'auteur - Warren J. Ewens

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.

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L'auteur - Gregory R. Grant

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.

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Caractéristiques techniques

  PAPIER
Éditeur(s) Springer
Auteur(s) Warren J. Ewens, Ewens, Gregory R. Grant
Parution 01/05/2001
Nb. de pages 476
Format 16 x 24
Couverture Relié
Poids 800g
Intérieur Noir et Blanc
EAN13 9780387952291
ISBN13 978-0-387-95229-1

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