A Kind of Agricultural Content Networking Information Fusion Method Based on Ontology. - Donghui Li; Cong Shen 002; Xiaopeng Dai; Haiwen Chen (ICCCS (4), 2018)

A Graph Convolutional Matrix Completion Method for miRNA-Disease Association Prediction. - Wei Wang; Jiawei Luo 001; Cong Shen 002; Nguyen Hoang Tu (ICIC (2), 2020)

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)

Identification of Small Molecule-miRNA Associations with Graph Regularization Techniques in Heterogeneous Networks. - Cong Shen 002; Jiawei Luo 001; Wenjue Ouyang; Pingjian Ding; Hao Wu (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)

IDDkin: network-based influence deep diffusion model for enhancing prediction of kinase inhibitors. - Cong Shen 002; Jiawei Luo 001; Wenjue Ouyang; Pingjian Ding; Xiangtao Chen (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)

scSAGAN: A scRNA-seq data imputation method based on Semi-Supervised Learning and Probabilistic Latent Semantic Analysis. - Zehao Xiong; Xiangtao Chen; Jiawei Luo 001; Cong Shen 002; Zhongyuan Xu (BIBM, 2022)

Multi-Relation Graph Embedding for Predicting miRNA-Target Gene Interactions by Integrating Gene Sequence Information. - Jiawei Luo 001; Wenjue Ouyang; Cong Shen 002; Jie Cai (IEEE J. Biomed. Health Informatics, 2022)

Diagnosis of Lung Cancer Subtypes by Combining Multi-graph Embedding and Graph Fusion Network. - Siyu Peng; Jiawei Luo 001; Cong Shen 002; Bo Wang (ICIC (5), 2023)

Curvature-enhanced Graph Convolutional Network for Biomolecular Interaction Prediction. - Cong Shen 002; Pingjian Ding; Junjie Wee; Jialin Bi; Jiawei Luo 001; Kelin Xia (CoRR, 2023)

Molecular geometric deep learning. - Cong Shen 002; Jiawei Luo 001; Kelin Xia (CoRR, 2023)

Fingerprint-Enhanced Graph Attention Network (FinGAT) Model for Antibiotic Discovery. - Hou Yee Choo; Junjie Wee; Cong Shen 002; Kelin Xia (J. Chem. Inf. Model., 2023)

Spatial-MGCN: a novel multi-view graph convolutional network for identifying spatial domains with attention mechanism. - Bo Wang; Jiawei Luo 001; Ying Liu 027; Wanwan Shi; Zehao Xiong; Cong Shen 002; Yahui Long (Briefings Bioinform., 2023)

Multitask joint learning with graph autoencoders for predicting potential MiRNA-drug associations. - Yichen Zhong; Cong Shen 002; Xiaoting Xi; Yuxun Luo; Pingjian Ding; Lingyun Luo (Artif. Intell. Medicine, 2023)

Multi-Cover Persistence (MCP)-based machine learning for polymer property prediction. - Yipeng Zhang; Cong Shen 002; Kelin Xia (Briefings Bioinform., 2024)

Molecular topological deep learning for polymer property prediction. - Cong Shen 002; Yipeng Zhang; Fei Han; Kelin Xia (CoRR, 2024)

Geometric Molecular Graph Representation Learning Model for Drug-Drug Interactions Prediction. - Zhenyu Jiang; Pingjian Ding; Cong Shen 002; Xiaopeng Dai (IEEE J. Biomed. Health Informatics, 2024)

Torsion Graph Neural Networks. - Cong Shen 002; Xiang Liu 021; Jiawei Luo 001; Kelin Xia (IEEE Trans. Pattern Anal. Mach. Intell., 2025)