Document Detail


Inference of transcriptional regulatory network by two-stage constrained space factor analysis.
MedLine Citation:
PMID:  16144806     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
MOTIVATION: Microarray gene expression and cross-linking chromatin immunoprecipitation data contain voluminous information that can help the identification of transcriptional regulatory networks at the full genome scale. Such high-throughput data are noisy however. In contrast, from the biomedical literature, we can find many evidenced transcription factor (TF)-target gene binding relationships that have been elucidated at the molecular level. But such sporadically generated knowledge only offers glimpses on limited patches of the network. How to incorporate this valuable knowledge resource to build more reliable network models remains a question. RESULTS: We present a modified factor analysis approach. Our algorithm starts with the evidenced TF-gene linkages. It iterates between the network configuration estimation step and the connection strength estimation step, using the high-throughput data, till convergence. We report two comprehensive regulatory networks obtained for Saccharomyces cerevisiae, one under the normal growth condition and the other under the environmental stress condition. SUPPLEMENTARY INFORMATION: http://kiefer.stat.ucla.edu/lap2/download/bti656_supplement.pdf.
Authors:
Tianwei Yu; Ker-Chau Li
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Publication Detail:
Type:  Journal Article; Research Support, U.S. Gov't, Non-P.H.S.     Date:  2005-09-06
Journal Detail:
Title:  Bioinformatics (Oxford, England)     Volume:  21     ISSN:  1367-4803     ISO Abbreviation:  Bioinformatics     Publication Date:  2005 Nov 
Date Detail:
Created Date:  2005-10-24     Completed Date:  2006-01-05     Revised Date:  2008-11-21    
Medline Journal Info:
Nlm Unique ID:  9808944     Medline TA:  Bioinformatics     Country:  England    
Other Details:
Languages:  eng     Pagination:  4033-8     Citation Subset:  IM    
Affiliation:
Department of Statistics, University of California-Los Angeles, Los Angeles, CA 90095-1554, USA.
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Computer Simulation
Factor Analysis, Statistical
Gene Expression Profiling / methods*
Gene Expression Regulation / physiology*
Models, Genetic*
Pattern Recognition, Automated / methods
Proteome / metabolism*
Signal Transduction / physiology*
Transcription Factors / metabolism*
Transcriptional Activation / physiology
Chemical
Reg. No./Substance:
0/Proteome; 0/Transcription Factors

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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