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Hidden Markov Models in Biology

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Book cover Data Mining Techniques for the Life Sciences

Part of the book series: Methods in Molecular Biology ((MIMB,volume 609))

Abstract

Markov and Hidden Markov models (HMMs) are introduced using examples from linkage mapping and sequence analysis. In the course, the forward–backward, the Viterbi, the Baum-Welch (EM) algorithm, and a Metropolis sampling scheme are presented.

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References

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Acknowledgments

CV’s work was funded in part by the FWF (SFB-F28) and AF’s work in part by the WWTF. CV wishes to thank the institute of animal breeding headed by Mathias Müller for support during the writing and especially Christian Schlötterer for encouragement and enthusiasm.

Author information

Authors and Affiliations

  1. Institute of Animal Breeding and Genetics, University of Veterinary Medicine Vienna, Vienna, Austria

    Claus Vogl

  2. Institute of Statistics, University of Vienna, Vienna, Austria

    Andreas Futschik

Authors
  1. Claus Vogl
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  2. Andreas Futschik
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Editor information

Editors and Affiliations

  1. Max F. Perutz Laboratories GmbH, Universität Wien, Dr. Bohr-Gasse 9, Wien, 1030, Austria

    Oliviero Carugo

  2. Research (A*STAR), Agency for Science & Technology, Biopolis Street 30, Singapore, 138671, Singapore

    Frank Eisenhaber

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© 2010 Humana Press, a part of Springer Science+Business Media, LLC

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Vogl, C., Futschik, A. (2010). Hidden Markov Models in Biology. In: Carugo, O., Eisenhaber, F. (eds) Data Mining Techniques for the Life Sciences. Methods in Molecular Biology, vol 609. Humana Press. https://doi.org/10.1007/978-1-60327-241-4_14

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  • DOI: https://doi.org/10.1007/978-1-60327-241-4_14

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  • Publisher Name: Humana Press

  • Print ISBN: 978-1-60327-240-7

  • Online ISBN: 978-1-60327-241-4

  • eBook Packages: Springer Protocols

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