4. Advances in Hidden Markov Models for Sequence Annotation

  1. Ion I. Mǎndoiu3 and
  2. Alexander Zelikovsky4
  1. Broňa Brejová1,
  2. Daniel G. Brown2 and
  3. Tomáš Vinař1

Published Online: 9 AUG 2007

DOI: 10.1002/9780470253441.ch4

Bioinformatics Algorithms: Techniques and Applications

Bioinformatics Algorithms: Techniques and Applications

How to Cite

Brejová, B., Brown, D. G. and Vinař, T. (2008) Advances in Hidden Markov Models for Sequence Annotation, in Bioinformatics Algorithms: Techniques and Applications (eds I. I. Mǎndoiu and A. Zelikovsky), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470253441.ch4

Editor Information

  1. 3

    Department of Computer Science and Engineering, University of Connecticut, Storrs, Connecticut, USA

  2. 4

    Department of Computer Science, Georgia State University, Atlanta, GA, USA

Author Information

  1. 1

    Department of Biological Statistics and Computational Biology, Cornell University, Ithaca, NY, USA

  2. 2

    Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada

Publication History

  1. Published Online: 9 AUG 2007
  2. Published Print: 8 FEB 2008

ISBN Information

Print ISBN: 9780470097731

Online ISBN: 9780470253441

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Keywords:

  • hidden Markov model (HMM);
  • single protein-coding gene;
  • sequence annotation problem

Summary

This chapter contains sections titled:

  • Introduction

  • Hidden Markov Models for Sequence Annotation

  • Alternatives to Viterbi Decoding

  • Generalized Hidden Markov Models

  • HMMs with Multiple Outputs or External Influences

  • Training the Parameters of an HMM

  • Conclusion

  • Acknowledgments

  • References