Predicting co-complexed protein pairs using genomic and proteomic data integration

BMC Bioinformatics

Volumn 5, Issue , 2004, Pages

  Zhang, Lan V ^a   Wong, Sharyl L ^a   King, Oliver D ^a   Roth, Frederick P ^a  

^a HARVARD MEDICAL SCHOOL   (United States)

Author keywords

Data integration; Decision tree; Machine learning; Protein complex; Protein protein interaction

Indexed keywords

AFFINITY PURIFICATION; EXPERIMENTAL VALIDATIONS; HIGH-THROUGHPUT METHOD; PHYSICAL INTERACTIONS; PROBABILISTIC DECISION TREES; PROTEIN COMPLEXES; PROTEIN-PROTEIN INTERACTIONS; SUPERVISED MACHINE LEARNING;

DATA INTEGRATION; DATA MINING; DECISION TREES; FORECASTING; GENES; LEARNING SYSTEMS; MASS SPECTROMETRY; MOLECULAR BIOLOGY; YEAST;

PROTEINS;

PROTEIN; FUNGAL RNA; SACCHAROMYCES CEREVISIAE PROTEIN;

ARTICLE; BIOINFORMATICS; GENOMICS; INFORMATION PROCESSING; MASS SPECTROMETRY; NONHUMAN; PREDICTION; PROBABILITY; PROTEIN ANALYSIS; PROTEIN DATABASE; PROTEIN PROTEIN INTERACTION; PROTEIN PURIFICATION; PROTEOMICS; SENSITIVITY AND SPECIFICITY; TWO HYBRID SYSTEM; VALIDATION PROCESS; BIOLOGY; BIOSYNTHESIS; DECISION TREE; FUNGAL GENE; GENE EXPRESSION REGULATION; GENETICS; METABOLISM; PREDICTIVE VALUE; PROCEDURES; STATISTICS AND NUMERICAL DATA; VALIDATION STUDY;

COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; DECISION TREES; GENE EXPRESSION REGULATION, FUNGAL; GENES, FUNGAL; GENOMICS; MASS SPECTROMETRY; PREDICTIVE VALUE OF TESTS; PROTEIN INTERACTION MAPPING; PROTEOMICS; RNA, FUNGAL; SACCHAROMYCES CEREVISIAE PROTEINS; TWO-HYBRID SYSTEM TECHNIQUES;

EID: 2942541277     PISSN: 14712105     EISSN: None     Source Type: Journal    
DOI: 10.1186/1471-2105-5-38     Document Type: Article

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