DR2DI: a powerful computational tool for predicting novel drug-disease associations

Title
DR2DI: a powerful computational tool for predicting novel drug-disease associations
Authors
Keywords
High-dimensional and heterogeneous omics data, Drug-disease associations, Drug repositioning, Regularized Kernel Classifier
Journal
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN
Volume 32, Issue 5, Pages 633-642
Publisher
Springer Nature
Online
2018-04-23
DOI
10.1007/s10822-018-0117-y

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