Mines large-scale chemical genomics and disease association data for prediction of novel drug-gene-disease associations. ANTENNA is a multi-rank, multi-layered recommender system that integrates a tri-factorization based dual-regularized weighted and imputes one class collaborative filtering (OCCF) algorithm with a statistical framework based on random walk with restart. It has three main components for: (1) integrating multiple chemical genomics and disease association data set, and linking them as a multi-layered network, (2) inferring genome-wide novel chemical-gene associations, and (3) predicting chemical-disease associations and assessing their reliabilities.
Bronx High School of Science, Bronx, NY, USA; Biochemistry, the City University of New York, New York, NY, USA; Department of Sciences, John Jay College, the City University of New York, New York, NY, USA; Department of Computer Science, Hunter College, and the Graduate Center, the City University of New York, New York, NY, USA
ANTENNA funding source(s)
Supported in part by Grant Number R01LM011986 from the National Library of Medicine (NLM) of the National Institute of Health (NIH), Grant Number R01GM122845 from the National Institute of General Medical Sciences (NIGMS) of the National Institute of Health (NIH), Grant Number R21TR001722 from the National Center for Advancing Translational Sciences of NIH, and Grant Number MD007599 from the National Institute on Minority Health and Health Disparities (NIMHD) of NIH.
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