Network-based drug-target interaction prediction with probabilistic soft logic

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 11, Issue 5, 2014, Pages 775-787

  Fakhraei, Shobeir ^a   Huang, Bert ^a   Raschid, Louiqa ^a   Getoor, Lise ^a,b  

^a UNIVERSITY OF MARYLAND   (United States)

^b University of California Santa Cruz   (United States)

Author keywords

Bipartite networks; Collective inference; Drug adverse effect prediction; Drug discovery; Drug repurposing; Drug target interaction prediction; Drug target prediction; Heterogeneous similarities; Hinge loss Markov random fields; Link prediction; Machine learning; Polypharmacology; Statistical relational learning; Systems biology

Indexed keywords

BIPARTITE NETWORK; COLLECTIVE INFERENCE; DRUG ADVERSE EFFECTS; DRUG DISCOVERY; DRUG TARGETS; DRUG-TARGET INTERACTIONS; HETEROGENEOUS SIMILARITIES; LINK PREDICTION; MARKOV RANDOM FIELDS; POLYPHARMACOLOGY; REPURPOSING; STATISTICAL RELATIONAL LEARNING; SYSTEMS BIOLOGY;

LEARNING SYSTEMS;

ADVERSE DRUG REACTION; AREA UNDER THE CURVE; BIOLOGY; CELL CULTURE; DRUG DELIVERY SYSTEM; DRUG DEVELOPMENT; DRUG INTERACTION; HUMAN; MACHINE LEARNING; PROCEDURES; REPRODUCIBILITY; STATISTICAL MODEL;

AREA UNDER CURVE; CELLS, CULTURED; COMPUTATIONAL BIOLOGY; DRUG DELIVERY SYSTEMS; DRUG DISCOVERY; DRUG INTERACTIONS; DRUG-RELATED SIDE EFFECTS AND ADVERSE REACTIONS; HUMANS; MACHINE LEARNING; MODELS, STATISTICAL; REPRODUCIBILITY OF RESULTS;

EID: 84907992703     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2014.2325031     Document Type: Article

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