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Gibbs sampling and bioinformatics

Part 4. Bioinformatics

4.8. Modern Programming Paradigms in Biology

Short Specialist Review

  1. Xiaole Shirley Liu

Published Online: 15 JUL 2005

DOI: 10.1002/047001153X.g409319

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

How to Cite

Liu, X. S. 2005. Gibbs sampling and bioinformatics. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. 4:4.8:106.

Author Information

  1. Dana-Farber Cancer Institute, Boston, MA, USA

Publication History

  1. Published Online: 15 JUL 2005

Abstract

Gibbs sampling is one of the best-known Markov chain Monte Carlo methods. Its first and most popular application to bioinformatics is the sequence motif finding problem. Since then, Gibbs sampling has been successfully applied to many other interesting genomics and bioinformatics problems, especially haplotype inference and microarray biclustering.

Keywords:

  • Gibbs sampling;
  • sequence motif finding;
  • haplotype inference;
  • microarray biclustering