Ontology highlight
ABSTRACT:
SUBMITTER: Hie B
PROVIDER: S-EPMC6519716 | biostudies-literature | 2018 Oct
REPOSITORIES: biostudies-literature
Science (New York, N.Y.) 20181001 6412
Although combining data from multiple entities could power life-saving breakthroughs, open sharing of pharmacological data is generally not viable because of data privacy and intellectual property concerns. To this end, we leverage modern cryptographic tools to introduce a computational protocol for securely training a predictive model of drug-target interactions (DTIs) on a pooled dataset that overcomes barriers to data sharing by provably ensuring the confidentiality of all underlying drugs, t ...[more]