A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae)

Proceedings of the National Academy of Sciences of the United States of America

Volumn 100, Issue 14, 2003, Pages 8348-8353

  Troyanskaya, Olga G ^a   Dolinski, Kara ^a   Owen, Art B ^b   Altman, Russ B ^a,c   Botstein, David ^a,d  

^a STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b STANFORD UNIVERSITY   (United States)

^c Princeton University ^*  (United States)

^d PRINCETON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

TRANSCRIPTION FACTOR;

ACCURACY; ARTICLE; BAYES THEOREM; DATA BASE; DNA DETERMINATION; DNA MICROARRAY; DNA TRANSCRIPTION; GENE EXPRESSION PROFILING; GENE FUNCTION; GENE INTERACTION; PREDICTION; PRIORITY JOURNAL; SACCHAROMYCES CEREVISIAE;

ALGORITHMS; BAYES THEOREM; BINDING SITES; GENES, FUNGAL; GENETIC TECHNIQUES; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PROTEIN INTERACTION MAPPING; SACCHAROMYCES CEREVISIAE; SACCHAROMYCES CEREVISIAE PROTEINS; SOFTWARE; TRANSCRIPTION FACTORS;

FUNGI; MYXOGASTRIA; SACCHAROMYCES; SACCHAROMYCES CEREVISIAE;

EID: 0038492417     PISSN: 00278424     EISSN: None     Source Type: Journal    
DOI: 10.1073/pnas.0832373100     Document Type: Article

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