The DTINET protocol is used to build a full heterogeneous graph and then learn a lowdimensional feature using matrix factorisation ( ). These approaches make DTINET outperform others; however, DTINET cannot predict the interaction of new compounds or targets ). Although they still have drawbacks, the example studies indicate that graph-based methods are competitive strategies to identify DTIs.