Research on drug-drug interaction (DDI) prediction, particularly in identifying DDI event
types, is crucial for understanding adverse drug reactions and drug combinations. This work …

Background Drug-target interaction (DTI) prediction plays a pivotal role in drug discovery
and drug repositioning, enabling the identification of potential drug candidates. However …

Multi-relational graph learning aims to embed entities and relations in knowledge graphs
into low-dimensional representations, which has been successfully applied to various multi …

Potential drug-drug interactions (DDI) can lead to adverse drug reactions (ADR), and DDI
prediction can help pharmacy researchers detect harmful DDI early. However, existing DDI …

Dynamic link prediction aims to predict future connections among unconnected nodes in a
network. It can be applied for friend recommendations, link completion, and other tasks …

Stock crash risk often propagates through various interconnected relationships between
firms, amplifying its impact across financial markets. Few studies predicted the crash risk of …

Multi-drug combination therapies are increasingly used for complex diseases but carry risks
of harmful drug interactions. Effective drug–drug interaction prediction (DDIP) is essential for …