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Statistical methods in bioinformatics : an introduction / Warren Ewens, Gregory Grant.

By: Contributor(s): Material type: TextTextSeries: Statistics for biology and healthPublication details: New York : Springer, 2005.Edition: 2nd edDescription: xx, 597 p. : ill. ; 24 cmISBN:
  • 9781441923028 (pbk.) :
  • 9780387266480 (ebook) :
  • 9781441923028 (Paper)
Subject(s): DDC classification:
  • 572.80285 EWE
LOC classification:
  • QH324.2 .E97 2005
Contents:
Preface. 1.Probability theory (i): One random variable -- 2.Probability theory (ii): Many random variables -- 3.Statistics (i):An introduction to statistical inference -- 4.Stochastic processess (i): Poisson processes and Markov chains -- 5.The analysis of one DNA sequence -- 6.The analysis of multiple DNA or protein sequences -- 7.Stochastic processess (ii): Random walks -- 8.Statistics (ii): Classical estimation theory -- 9.Statistics (iii): Classical hypothesis testing theory -- 10.Blast -- 11.Stochastic processes (iii): Markov chains -- 12.Hidden Markov models -- 13.Gene expression, microarrays, and mutiple testing -- 14.Evolutionary models -- 15.Phylogenetic tree estimation -- Appendix A.Basic notions in biology -- Appendix B.Mathematical formulae and results.
Summary: Advances in computers & biotechnology have had a profound impact on biomedical research, & as a result complex data sets can now be generated to address extremely complex biological questions. This text includes methods important in the analysis of human genome data.
Holdings
Item type Current library Call number Copy number Status Date due Barcode
Long Loan TUS: Midlands, Main Library Athlone General Lending 572.80285 EWE (Browse shelf(Opens below)) 1 Available 217009

Includes bibliographical references and index.

Preface. 1.Probability theory (i): One random variable -- 2.Probability theory (ii): Many random variables -- 3.Statistics (i):An introduction to statistical inference -- 4.Stochastic processess (i): Poisson processes and Markov chains -- 5.The analysis of one DNA sequence -- 6.The analysis of multiple DNA or protein sequences -- 7.Stochastic processess (ii): Random walks -- 8.Statistics (ii): Classical estimation theory -- 9.Statistics (iii): Classical hypothesis testing theory -- 10.Blast -- 11.Stochastic processes (iii): Markov chains -- 12.Hidden Markov models -- 13.Gene expression, microarrays, and mutiple testing -- 14.Evolutionary models -- 15.Phylogenetic tree estimation -- Appendix A.Basic notions in biology -- Appendix B.Mathematical formulae and results.

Advances in computers & biotechnology have had a profound impact on biomedical research, & as a result complex data sets can now be generated to address extremely complex biological questions. This text includes methods important in the analysis of human genome data.

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