Drug-target interaction prediction using semi-bipartite graph model and deep learning

摘要

Prediction of Drug-Target Interactions (DTI) is a critical part of drug discovery in pharmaceutical research. Compared to biochemical experimental methods which are laborious, time consuming and extremely expensive, computational methods are of high interest because they can efficiently identify potential DTIs or narrow down the search space for biologists and biochemists.