An adaptive graph learning method for automated molecular interactions and properties predictions. - Yuquan Li; Chang-Yu Hsieh; Ruiqiang Lu; Xiaoqing Gong; Xiaorui Wang; Pengyong Li; Shuo Liu; Yanan Tian; Dejun Jiang 002; Jiaxian Yan; Qifeng Bai; Huanxiang Liu; et al. (Nat. Mach. Intell., 2022)

RHGN: Relation-gated Heterogeneous Graph Network for Entity Alignment in Knowledge Graphs. - Xukai Liu; Kai Zhang 038; Ye Liu 011; Enhong Chen; Zhenya Huang; Linan Yue; Jiaxian Yan (ACL (Findings), 2023)

A Systematic Survey in Geometric Deep Learning for Structure-based Drug Design. - Zaixi Zhang; Jiaxian Yan; Qi Liu 003; Enhong Chen (CoRR, 2023)

Multi-scale Iterative Refinement towards Robust and Versatile Molecular Docking. - Jiaxian Yan; Zaixi Zhang; Kai Zhang 038; Qi Liu 003 (CoRR, 2023)

Multi-task bioassay pre-training for protein-ligand binding affinity prediction. - Jiaxian Yan; Zhaofeng Ye; Ziyi Yang; Chengqiang Lu; Shengyu Zhang; Qi Liu; Jiezhong Qiu (Briefings Bioinform., 2023)

DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular Docking. - Jiaxian Yan; Zaixi Zhang; Jintao Zhu; Kai Zhang 038; Jianfeng Pei; Qi Liu 003 (NeurIPS, 2024)