Predicting drug-disease associations by using similarity constrained matrix factorization

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...