EDDINet: Enhancing drug-drug interaction prediction via information flow and consensus constrained multi-graph contrastive learning

Hong Wang, Luhe Zhuang, Yijie Ding, Prayag Tiwari, Cheng Liang

Abstract: Highlights•EDDINet is proposed via Information Flow and Consensus-Constrained Multi-Graph Contrastive Learning.•Introduce the cross-modal information-flow mechanism to facilitate the information across various drug features.•EDDINet surpasses state-of-the-art unsupervised models and even outperforms some supervised baseline models in DDI prediction tasks.