Discovering molecular pathways from protein interaction and gene expression data

Bioinformatics

Volumn 19, Issue SUPPL. 1, 2003, Pages

  Segal, E ^a   Wang, H ^a   Koller, D ^a  

^a Stanford University   (United States)

Author keywords

Gene expression; Probabilistic models; Protein interaction

Indexed keywords

ALGORITHM; CONFERENCE PAPER; GENE EXPRESSION; MOLECULAR BIOLOGY; NONHUMAN; PRIORITY JOURNAL; PROBABILITY; PROTEIN INTERACTION; SACCHAROMYCES CEREVISIAE; ARTICLE; ARTIFICIAL INTELLIGENCE; BIOLOGICAL MODEL; COMPARATIVE STUDY; COMPUTER INTERFACE; CYTOLOGY; EVALUATION; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETICS; METABOLISM; METHODOLOGY; PHYSIOLOGY; PROTEIN ANALYSIS; SIGNAL TRANSDUCTION; STATISTICAL MODEL; SYSTEM ANALYSIS; VALIDATION STUDY;

SACCHAROMYCES CEREVISIAE;

SACCHAROMYCES CEREVISIAE PROTEIN;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PROTEIN INTERACTION MAPPING; SACCHAROMYCES CEREVISIAE; SACCHAROMYCES CEREVISIAE PROTEINS; SIGNAL TRANSDUCTION; SYSTEMS INTEGRATION; USER-COMPUTER INTERFACE;

EID: 0842309161     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btg1037     Document Type: Conference Paper

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