A supervised hidden markov model framework for efficiently segmenting tiling array data in transcriptional and chIP-chip experiments: systematically incorporating validated biological knowledge.

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Bibliographic Details
Title: A supervised hidden markov model framework for efficiently segmenting tiling array data in transcriptional and chIP-chip experiments: systematically incorporating validated biological knowledge.
Authors: Du J; Department of Computer Science, Yale University, New Haven, CT 06520, USA., Rozowsky JS, Korbel JO, Zhang ZD, Royce TE, Schultz MH, Snyder M, Gerstein M
Source: Bioinformatics (Oxford, England) [Bioinformatics] 2006 Dec 15; Vol. 22 (24), pp. 3016-24. Date of Electronic Publication: 2006 Oct 12.
Publication Type: Evaluation Study; Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Validation Study
Journal Info: Publisher: Oxford University Press Country of Publication: England NLM ID: 9808944 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1367-4811 (Electronic) Linking ISSN: 13674803 NLM ISO Abbreviation: Bioinformatics Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1367-4811
DOI:10.1093/bioinformatics/btl515