Drug repositioning through integration of prior knowledge and projections of drugs and diseases. - Ping Xuan; Yangkun Cao; Tiangang Zhang; Xiao Wang; Shuxiang Pan; Tonghui Shen (Bioinform., 2019)

Autoencoder-based drug-target interaction prediction by preserving the consistency of chemical properties and functions of drugs. - Chang Sun 002; Yangkun Cao; Jin-Mao Wei 001; Jian Liu (Bioinform., 2021)

Multi-channel graph attention autoencoders for disease-related lncRNAs prediction. - Nan Sheng; Lan Huang 002; Yan Wang 028; Jing Zhao; Ping Xuan; Ling Gao; Yangkun Cao (Briefings Bioinform., 2022)

Learning multi-scale heterogenous network topologies and various pairwise attributes for drug-disease association prediction. - Hongda Zhang; Hui Cui 002; Tiangang Zhang; Yangkun Cao; Ping Xuan (Briefings Bioinform., 2022)

MORGAT: A Model Based Knowledge-Informed Multi-omics Integration and Robust Graph Attention Network for Molecular Subtyping of Cancer. - Haobo Shi; Yujie Gu; Hengyuan Zhang; Xuan Li; Yangkun Cao (ICIC (3), 2023)

A Survey of Computational Methods and Databases for lncRNA-MiRNA Interaction Prediction. - Nan Sheng; Lan Huang 002; Ling Gao; Yangkun Cao; Xuping Xie; Yan Wang 028 (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

Multi-task prediction-based graph contrastive learning for inferring the relationship among lncRNAs, miRNAs and diseases. - Nan Sheng; Yan Wang 028; Lan Huang 002; Ling Gao; Yangkun Cao; Xuping Xie; Yuan Fu (Briefings Bioinform., 2023)

X-LDA: An interpretable and knowledge-informed heterogeneous graph learning framework for LncRNA-disease association prediction. - Yangkun Cao; Jun Xiao; Nan Sheng; Yinwei Qu; Zhihang Wang; Chang Sun 002; Xuechen Mu; Zhenyu Huang; Xuan Li (Comput. Biol. Medicine, 2023)

Estimating Individual Causal Treatment Effect by Variable Decomposition. - Hongyang Jiang 002; Yonghe Zhao; Qiang Huang; Yangkun Cao; Huiyan Sun; Yi Chang 001 (IJCNN, 2024)