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Unsupervised segmentation of continuous genomic data.

The advent of high-density, high-volume genomic data has created the need for tools to summarize large datasets at multiple scales. HMMSeg is a command-line utility for the scale-specific segmentation of continuous genomic data using hidden Markov models (HMMs). Scale specificity is achieved by an optional wavelet-based smoothing operation. HMMSeg is capable of handling multiple datasets simultaneously, rendering it ideal for integrative analysis of expression, phylogenetic and functional genomic data. AVAILABILITY: http://noble.gs.washington.edu/proj/hmmseg

Pubmed ID: 17384021


  • Day N
  • Hemmaplardh A
  • Thurman RE
  • Stamatoyannopoulos JA
  • Noble WS


Bioinformatics (Oxford, England)

Publication Data

June 1, 2007

Associated Grants

  • Agency: NIGMS NIH HHS, Id: R01 GM071923
  • Agency: NIGMS NIH HHS, Id: R01 GM71852
  • Agency: NHGRI NIH HHS, Id: U01 HG003161

Mesh Terms

  • Algorithms
  • Artificial Intelligence
  • Chromosome Mapping
  • Computer Simulation
  • Databases, Genetic
  • Information Storage and Retrieval
  • Markov Chains
  • Models, Genetic
  • Models, Statistical
  • Pattern Recognition, Automated
  • Sequence Analysis, DNA