Predicting protein functions through non-negative matrix factorization regularized by protein-protein interaction network and gene functional information. - Wei Peng 004; Lun Li; Wei Dai 012; Jielin Du; Wei Lan (BIBM, 2019)

Identifying Human Essential Genes by Network Embedding Protein-Protein Interaction Network. - Wei Dai 012; Qi Chang; Wei Peng 004; Jiancheng Zhong; Yongjiang Li (ISBRA, 2019)

Improving Identification of Essential Proteins by a Novel Ensemble Method. - Wei Dai 012; Xia Li 004; Wei Peng 004; Jurong Song; Jiancheng Zhong; Jianxin Wang 001 (ISBRA, 2019)

A multi-view approach for predicting microbedisease associations by fusing the linear and nonlinear features. - Ming Liu; Wei Dai 012; Wei Peng 004; Yu Fu; Yi Pan 001 (BIBM, 2020)

Predicting protein functions by using non-negative matrix factorisation with multi-networks co-regularisation. - Wei Peng 004; Jielin Du; Lun Li; Wei Dai 012; Wei Lan (Int. J. Data Min. Bioinform., 2020)

A Heterogeneous Graph Convolutional Network-Based Deep Learning Model to Identify miRNA-Disease Association. - Zicheng Che; Wei Peng 004; Wei Dai 012; Shoulin Wei; Wei Lan (ISBRA, 2021)

A Novel Multi-Ensemble Method for Identifying Essential Proteins. - Wei Dai 012; Bingxi Chen; Wei Peng 004; Xia Li 004; Jiancheng Zhong; Jianxin Wang 001 (J. Comput. Biol., 2021)

Identification of personalized driver genes for individuals using graph convolution network. - Wei Peng 004; Piaofang Yu; Wei Dai 012; Xiaodong Fu; Li Liu 032; Yi Pan 001 (BIBM, 2022)

Improving cancer driver gene identification using multi-task learning on graph convolutional network. - Wei Peng 004; Qi Tang; Wei Dai 012; Tielin Chen (Briefings Bioinform., 2022)

Predicting cancer drug response using parallel heterogeneous graph convolutional networks with neighborhood interactions. - Wei Peng 004; Hancheng Liu; Wei Dai 012; Ning Yu 004; Jianxin Wang 001 (Bioinform., 2022)

Predicting Drug Response Based on Multi-Omics Fusion and Graph Convolution. - Wei Peng 004; Tielin Chen; Wei Dai 012 (IEEE J. Biomed. Health Informatics, 2022)

A multi-view comparative learning method for spatial transcriptomics data clustering. - Wei Peng 004; Zhihao Zhang; Wei Dai 012; Xiaodong Fu; Li Liu 032; Lijun Liu; Ning Yu 004 (BIBM, 2023)

Predicting miRNA-Disease Associations From miRNA-Gene-Disease Heterogeneous Network With Multi-Relational Graph Convolutional Network Model. - Wei Peng 004; Zicheng Che; Wei Dai 012; Shoulin Wei; Wei Lan (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

Multi-View Feature Aggregation for Predicting Microbe-Disease Association. - Wei Peng 004; Ming Liu; Wei Dai 012; Tielin Chen; Yu Fu; Yi Pan 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

Improving drug response prediction based on two-space graph convolution. - Wei Peng 004; Tielin Chen; Hancheng Liu; Wei Dai 012; Ning Yu 004; Wei Lan (Comput. Biol. Medicine, 2023)

Identifying cancer driver genes based on multi-view heterogeneous graph convolutional network and self-attention mechanism. - Wei Peng 004; Rong Wu; Wei Dai 012; Ning Yu 004 (BMC Bioinform., 2023)

Sparse Attention-based Hierarchical Node Representation for Spatial Domain Identification. - Wei Peng 004; Zhihao Ping; Wei Dai 012; Xiaodong Fu; Li Liu 032; Lijun Liu; Ning Yu 004 (BIBM, 2024)

Patient Anticancer Drug Response Prediction Based on Single-Cell Deconvolution. - Wei Peng 004; Chuyue Chen; Wei Dai 012 (ISBRA (3), 2024)

Hypergraph Representation Learning for Cancer Drug Response Prediction. - Wei Peng 004; Jiangzhen Lin; Wei Dai 012; Gong Chen; Xiaodong Fu; Li Liu 032; Lijun Liu (ISBRA (2), 2024)

DGCL: A Contrastive Learning Method for Predicting Cancer Driver Genes Based on Graph Diffusion. - Wei Peng 004; Zhengnan Zhou; Wei Dai 012; Xinping Xu; Xiaodong Fu; Li Liu 032; Lijun Liu (ISBRA (2), 2024)

Multi-Network Graph Contrastive Learning for Cancer Driver Gene Identification. - Wei Peng 004; Zhengnan Zhou; Wei Dai 012; Ning Yu 004; Jianxin Wang 001 (IEEE Trans. Netw. Sci. Eng., 2024)

A Study of Classroom Behavior Recognition Incorporating Super-Resolution and Target Detection. - Xiaoli Zhang; Jialei Nie; Shoulin Wei; Guifu Zhu; Wei Dai 012; Can Yang (Sensors, 2024)

Supervised graph contrastive learning for cancer subtype identification through multi-omics data integration. - Fangxu Chen; Wei Peng 004; Wei Dai 012; Shoulin Wei; Xiaodong Fu; Li Liu 032; Lijun Liu (Health Inf. Sci. Syst., 2024)

A Survival Prediction Model Integrating Hierarchical Pathological Image and Pathway Features. - Xinyue Xu; Wei Peng 004; Wei Dai 012; Xiaodong Fu; Li Liu 032; Lijun Liu (ISBRA (2), 2025)

Fusion of brain imaging genetic data for alzheimer's disease diagnosis and causal factors identification using multi-stream attention mechanisms and graph convolutional networks. - Wei Peng 004; Yanhan Ma; Chunshan Li; Wei Dai 012; Xiaodong Fu; Li Liu 032; Lijun Liu; Jin Liu 012 (Neural Networks, 2025)

Predicting Clinical Anticancer Drug Response of Patients by Using Domain Alignment and Prototypical Learning. - Wei Peng 004; Chuyue Chen; Wei Dai 012; Ning Yu 004; Jianxin Wang 001 (IEEE J. Biomed. Health Informatics, 2025)

Prediction of miRNA-disease association based on heterogeneous hypergraph convolution and heterogeneous graph multi-scale convolution. - Wei Dai 012; Sifan Pang; Zhichen He; Xiaodong Fu; Li Liu 032; Lijun Liu; Ning Yu 004 (Health Inf. Sci. Syst., 2025)