Unsupervised segmentation of continuous genomic data.

Unsupervised segmentation of continuous genomic data. Research Abstract Details 

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Unsupervised segmentation of continuous genomic data. Abstract Text:

Nathan Day,Andrew Hemmaplardh,Robert E Thurman,John A Stamatoyannopoulos,William S Noble,

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

Unsupervised segmentation of continuous genomic data. Publishing Authors By Initials

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

For similar investigative techniques: genetic techniques: sequence analysis: sequence analysis, dna research abstracts see: investigative techniques: genetic techniques: sequence analysis: sequence analysis, dna research

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Unsupervised segmentation of continuous genomic data. Journal Published:

PUBLICATION TYPE: Research Support, N.I.H., Extr

Journal: Bioinformatics (Oxford, England)

VOLUME: 23

Page Numbers: 1424-6

Journal Abbreviation: Bioinformatics

ISSN: 1460-2059

DAY: 23

MONTH: 03

YEAR: 2007

Unsupervised segmentation of continuous genomic data. Information

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LANGUAGE: eng

NlmUniqueID: 9808944

Unsupervised segmentation of continuous genomic data. Keywords Mesh Terms:

KEYWORDS: Sequence Analysis, DNA

MESH TERMS: methods

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Grant and Affiliation Information for Unsupervised segmentation of continuous genomic data.

AFFILIATION: Department of Computer Science and Engineering, University of Washington, Seattle, WA, USA.

Country: England

AGENCY: United States NHGRI

GRANT: U01 HG003161

ACRONYM: HG

MEDLINETA: Bioinformatics

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