Incorporating Multisource Knowledge To Predict Drug Synergy Based on Graph Co-regularization. - Pingjian Ding; Cong Shen 002; Zihan Lai; Cheng Liang 001; Guanghui Li 003; Jiawei Luo 001 (J. Chem. Inf. Model., 2020)

Multiview Joint Learning-Based Method for Identifying Small-Molecule-Associated MiRNAs by Integrating Pharmacological, Genomics, and Network Knowledge. - Cong Shen 002; Jiawei Luo 001; Zihan Lai; Pingjian Ding (J. Chem. Inf. Model., 2020)

Graph Attention Mechanism-based Deep Tensor Factorization for Predicting disease-associated miRNA-miRNA pairs. - Jiawei Luo 001; Zihan Lai; Cong Shen 002; Pei Liu; Heyuan Shi (BIBM, 2021)

Multi-view Multichannel Attention Graph Convolutional Network for miRNA-disease association prediction. - Xinru Tang; Jiawei Luo 001; Cong Shen 002; Zihan Lai (Briefings Bioinform., 2021)

Incorporating Clinical, Chemical and Biological Information for Predicting Small Molecule-microRNA Associations Based on Non-Negative Matrix Factorization. - Jiawei Luo 001; Cong Shen 002; Zihan Lai; Jie Cai; Pingjian Ding (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Research on the Mechanism of Cooperative Defense Against DDoS Attacks Based on Game Theory. - Tong Wang; Zihan Lai; Weiqing Yu; Zhijun Wu 001 (DataCom, 2022)

Multi-source Data-Based Deep Tensor Factorization for Predicting Disease-Associated miRNA Combinations. - Sheng You; Zihan Lai; Jiawei Luso (ICIC (2), 2022)

Data Integration Using Tensor Decomposition for the Prediction of miRNA-Disease Associations. - Jiawei Luo 001; Yi Liu; Pei Liu; Zihan Lai; Hao Wu (IEEE J. Biomed. Health Informatics, 2022)