An integrative multi-network and multi-classifier approach to predict genetic interactions

PLoS Computational Biology

Volumn 6, Issue 9, 2010, Pages

  Pandey, Gaurav ^a,d   Zhang, Bin ^b,c   Chang, Aaron N ^b,e   Myers, Chad L ^a   Zhu, Jun ^b,c   Kumar, Vipin ^a   Schadt, Eric E ^b,f  

^a University of Minnesota   (United States)

^b ROSETTA INPHARMATICS   (United States)

^c SAGE BIONETWORKS   (United States)

^d UNIVERSITY OF CALIFORNIA   (United States)

^e REGULUS THERAPEUTICS   (United States)

^f PACIFIC BIOSCIENCES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); FORECASTING; TRANSCRIPTION;

DATA-SOURCE; FUNCTIONAL REDUNDANCY; GENETIC INTERACTION; HUMAN DISEASE; MECHANISTICS; MULTI-CLASSIFIER; MUTATION RESULTS; NETWORK CLASSIFIERS; PROTEIN COMPLEXES; SYNTHETIC LETHAL;

YEAST;

FUNGAL PROTEIN; TRANSCRIPTION FACTOR;

ACCURACY; ANALYTIC METHOD; ARTICLE; CALCULATION; CONTROLLED STUDY; GENE INTERACTION; GENETIC DATABASE; HUMAN; INFORMATION PROCESSING; INFORMATION RETRIEVAL; INTERMETHOD COMPARISON; MULTI CLASSIFIER APPROACH; MULTI NETWORK APPROACH; NONHUMAN; PREDICTION; VALIDITY;

EID: 78049415626     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1000928     Document Type: Article

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