A subspace learning aided matrix factorization for drug repurposing

The proposed matrix factorization based method for drug repurposing, benefits from integrating knowledge from two domains, drug-disease and drug-target domains, and also is capable of preserve the geometry of the data in both feature space, and s ample space. Comparing to existing state of the art methods, this shows accuracy improvement in drug repurposing.