| Literature DB >> 17384021 |
Nathan Day1, Andrew Hemmaplardh, Robert E Thurman, John A Stamatoyannopoulos, William S Noble.
Abstract
UNLABELLED: 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/hmmsegMesh:
Year: 2007 PMID: 17384021 DOI: 10.1093/bioinformatics/btm096
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937