  We report development of a data infrastructure for drug repurposing that
takes advantage of two currently available chemical ontologies. The data
infrastructure includes a database of compound- target associations augmented
with molecular ontological labels. It also contains two computational tools for
prediction of new associations. We describe two drug-repurposing systems: one,
Nascent Ontological Information Retrieval for Drug Repurposing (NOIR-DR), based
on an information retrieval strategy, and another, based on non-negative matrix
factorization together with compound similarity, that was inspired by
recommender systems. We report the performance of both tools on a
drug-repurposing task.
