KGExplainer: Towards Exploring Connected Subgraph Explanations for Knowledge Graph Completion

no code implementations • 5 Apr 2024 • Tengfei Ma, Xiang Song, Wen Tao, Mufei Li, Jiani Zhang, Xiaoqin Pan, Jianxin Lin, Bosheng Song, Xiangxiang Zeng

Knowledge graph completion (KGC) aims to alleviate the inherent incompleteness of knowledge graphs (KGs), which is a critical task for various applications, such as recommendations on the web.

Knowledge Graph Embedding

Deep learning for drug repurposing: methods, databases, and applications

no code implementations • 8 Feb 2022 • Xiaoqin Pan, Xuan Lin, Dongsheng Cao, Xiangxiang Zeng, Philip S. Yu, Lifang He, Ruth Nussinov, Feixiong Cheng

Drug development is time-consuming and expensive.

Repurpose Open Data to Discover Therapeutics for COVID-19 using Deep Learning

no code implementations • 21 May 2020 • Xiangxiang Zeng, Xiang Song, Tengfei Ma, Xiaoqin Pan, Yadi Zhou, Yuan Hou, Zheng Zhang, George Karypis, Feixiong Cheng

While this study, by no means recommends specific drugs, it demonstrates a powerful deep learning methodology to prioritize existing drugs for further investigation, which holds the potential of accelerating therapeutic development for COVID-19.