A Bayesian approach to reconstructing genetic regulatory networks with hidden factors

Bioinformatics

Volumn 21, Issue 3, 2005, Pages 349-356

  Beal, Matthew J ^a   Falciani, Francesco ^b   Ghahramani, Zoubin ^c   Rangel, Claudia ^d,e   Wild, David L ^d  

^a the State University of New York   (United States)

^b UNIVERSITY OF BIRMINGHAM   (United Kingdom)

^c UNIVERSITY COLLEGE LONDON   (United Kingdom)

^d KECK GRADUATE INSTITUTE   (United States)

^e UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

IONOMYCIN; MESSENGER RNA; REGULATOR PROTEIN;

ANALYTIC METHOD; APOPTOSIS; ARTICLE; BAYES THEOREM; CELL FUNCTION; CLONAL VARIATION; CONFIDENCE INTERVAL; CONTROLLED STUDY; DNA MICROARRAY; GENE CONTROL; GENE EXPRESSION PROFILING; GENE INTERACTION; GENE REPLICATION; GENETIC ENGINEERING; GENETIC TRANSCRIPTION; HUMAN; HUMAN CELL; INTERMETHOD COMPARISON; LYMPHOCYTE PROLIFERATION; MATHEMATICAL MODEL; MATHEMATICAL PARAMETERS; PRIORITY JOURNAL; PROBABILITY; PROTEIN DEGRADATION; T LYMPHOCYTE ACTIVATION; TIME SERIES ANALYSIS; VARIANCE;

EID: 13844253637     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/bti014     Document Type: Article

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