• Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes

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

Authors

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

Journal

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