Original paper
Predicting drug-disease associations by using similarity constrained matrix factorization
Abstract
Drug-disease associations provide important information for the drug discovery. Wet experiments that identify drug-disease associations are time-consuming and expensive. However, many drug-disease associations are still unobserved or unknown. The development of computational methods for predicting unobserved drug-disease associations is an important and urgent task. In this paper, we proposed a similarity constrained matrix factorization method...
Paper Details
Title
Predicting drug-disease associations by using similarity constrained matrix factorization
Published Date
Jun 19, 2018
Journal
Volume
19
Issue
1
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Notes
History