An unsupervised approach to predict functional relations between genes based on expression data

BioMed Research International

Volumn 2014, Issue , 2014, Pages

  Altaf Ul Amin, Md ^a   Katsuragi, Tetsuo ^a   Sato, Tetsuo ^a   Ono, Naoaki ^a   Kanaya, Shigehiko ^a  

^a NARA INSTITUTE OF SCIENCE AND TECHNOLOGY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

TRANSCRIPTION FACTOR; SACCHAROMYCES CEREVISIAE PROTEIN;

ARTICLE; BINDING SITE; DENSITY; FUNGAL GENE; GENE; GENE EXPRESSION; GENE EXPRESSION PROFILING; GENE FUNCTION; HYBRIDIZATION; MASS; MICROARRAY ANALYSIS; NONHUMAN; PROBABILITY; PROMOTER REGION; SACCHAROMYCES CEREVISIAE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPUTER SIMULATION; GENE EXPRESSION REGULATION; METABOLISM; MULTIGENE FAMILY; PHYSIOLOGY; PROCEDURES; PROTEIN ANALYSIS; SIGNAL TRANSDUCTION;

ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; GENE EXPRESSION REGULATION; MODELS, BIOLOGICAL; MULTIGENE FAMILY; PATTERN RECOGNITION, AUTOMATED; PROTEIN INTERACTION MAPPING; SACCHAROMYCES CEREVISIAE; SACCHAROMYCES CEREVISIAE PROTEINS; SIGNAL TRANSDUCTION; TRANSCRIPTION FACTORS;

EID: 84899581898     PISSN: 23146133     EISSN: 23146141     Source Type: Journal    
DOI: 10.1155/2014/154594     Document Type: Article

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