springD2A: capturing uncertainty in disease-drug association prediction with model integration

Weiwen Wang, Xiwen Zhang, Dao-Qing Dai

Abstract: Drug repositioning that aims to find new indications for existing drugs has been an efficient strategy for drug discovery. In the scenario where we only have confirmed disease–drug associations as positive pairs, a negative set of disease–drug pairs is usually constructed from the unknown disease–drug pairs in previous studies, where we do not know whether drugs and diseases can be associated, to train a model for disease–drug association prediction (drug repositioning). Drugs and diseases in these negative pairs can potentially be associated, but most studies have ignored them.