A non-negative matrix factorization based method for predicting disease-associated miRNAs in miRNA-disease bilayer network. - Yingli Zhong; Ping Xuan; Xiao Wang; Tiangang Zhang; Jianzhong Li 001; Yong Liu 029; Weixiong Zhang (Bioinform., 2018)

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)

Assistant diagnosis with Chinese electronic medical records based on CNN and BiLSTM with phrase-level and word-level attentions. - Tong Wang; Ping Xuan; Zonglin Liu; Tiangang Zhang (BMC Bioinform., 2020)

Inferring Disease-Associated microRNAs in Heterogeneous Networks with Node Attributes. - Ping Xuan; Tonghui Shen; Xiao Wang; Tiangang Zhang; Weixiong Zhang (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

Integrating Channel Context Attention and Regional Association Attention for Kidney and Tumor Segmentation. - Ying Liu; Hui Cui 002; Tiangang Zhang; Toshiya Nakaguchi; Ping Xuan (EMBC, 2021)

Attentional multi-level representation encoding based on convolutional and variance autoencoders for lncRNA-disease association prediction. - Nan Sheng; Hui Cui 002; Tiangang Zhang; Ping Xuan (Briefings Bioinform., 2021)

Integrating multi-scale neighbouring topologies and cross-modal similarities for drug-protein interaction prediction. - Ping Xuan; Yu Zhang; Hui Cui 002; Tiangang Zhang; Maozu Guo 001; Toshiya Nakaguchi (Briefings Bioinform., 2021)

Prediction of Drug-Target Interactions Based on Network Representation Learning and Ensemble Learning. - Ping Xuan; Bingxu Chen; Tiangang Zhang; Yan Yang (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

Graph Convolutional Autoencoder and Fully-Connected Autoencoder with Attention Mechanism Based Method for Predicting Drug-Disease Associations. - Ping Xuan; Ling Gao; Nan Sheng; Tiangang Zhang; Toshiya Nakaguchi (IEEE J. Biomed. Health Informatics, 2021)

Prediction of drug-disease associations by integrating common topologies of heterogeneous networks and specific topologies of subnets. - Ling Gao; Hui Cui 002; Tiangang Zhang; Nan Sheng; Ping Xuan (Briefings Bioinform., 2022)

ALDPI: adaptively learning importance of multi-scale topologies and multi-modality similarities for drug-protein interaction prediction. - Kaimiao Hu; Hui Cui 002; Tiangang Zhang; Chang Sun 002; Ping Xuan (Briefings Bioinform., 2022)

GVDTI: graph convolutional and variational autoencoders with attribute-level attention for drug-protein interaction prediction. - Ping Xuan; Mengsi Fan; Hui Cui 002; Tiangang Zhang; Toshiya Nakaguchi (Briefings Bioinform., 2022)

Fully connected autoencoder and convolutional neural network with attention-based method for inferring disease-related lncRNAs. - Ping Xuan; Zhe Gong; Hui Cui 002; Bochong Li; Tiangang Zhang (Briefings Bioinform., 2022)

Heterogeneous multi-scale neighbor topologies enhanced drug-disease association prediction. - Ping Xuan; Xiangfeng Meng; Ling Gao; Tiangang Zhang; Toshiya Nakaguchi (Briefings Bioinform., 2022)

Integration of pairwise neighbor topologies and miRNA family and cluster attributes for miRNA-disease association prediction. - Ping Xuan; Dong Wang; Hui Cui 002; Tiangang Zhang; Toshiya Nakaguchi (Briefings Bioinform., 2022)

Learning global dependencies and multi-semantics within heterogeneous graph for predicting disease-related lncRNAs. - Ping Xuan; Shuai Wang 038; Hui Cui 002; Yue Zhao; Tiangang Zhang; Peiliang Wu (Briefings Bioinform., 2022)

Integrating specific and common topologies of heterogeneous graphs and pairwise attributes for drug-related side effect prediction. - Ping Xuan; Meng Wang; Yong Liu; Dong Wang; Tiangang Zhang; Toshiya Nakaguchi (Briefings Bioinform., 2022)

multi-type neighbors enhanced global topology and pairwise attribute learning for drug-protein interaction prediction. - Ping Xuan; Xiaowen Zhang; Yu Zhang; Kaimiao Hu; Toshiya Nakaguchi; Tiangang Zhang (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)

Convolutional bi-directional learning and spatial enhanced attentions for lung tumor segmentation. - Ping Xuan; Bin Jiang; Hui Cui 002; Qiangguo Jin; Peng Cheng; Toshiya Nakaguchi; Tiangang Zhang; Changyang Li; Zhiyu Ning; Menghan Guo; Linlin Wang (Comput. Methods Programs Biomed., 2022)

Dynamic graph convolutional autoencoder with node-attribute-wise attention for kidney and tumor segmentation from CT volumes. - Ping Xuan; Hui Cui 002; Hongda Zhang; Tiangang Zhang; Linlin Wang; Toshiya Nakaguchi; Henry B. L. Duh (Knowl. Based Syst., 2022)

Prediction of Drug-Related Diseases Through Integrating Pairwise Attributes and Neighbor Topological Structures. - Yingying Song; Hui Cui 002; Tiangang Zhang; Tingxiao Yang; Xiaokun Li; Ping Xuan (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

Graph Convolutional Autoencoder and Generative Adversarial Network-Based Method for Predicting Drug-Target Interactions. - Chang Sun 002; Ping Xuan; Tiangang Zhang; Yilin Ye (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

Inferring Drug-Target Interactions Based on Random Walk and Convolutional Neural Network. - Xiaoqiang Xu; Ping Xuan; Tiangang Zhang; Bingxu Chen; Nan Sheng (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

Learning Multi-Scale Heterogeneous Representations and Global Topology for Drug-Target Interaction Prediction. - Ping Xuan; Kaimiao Hu; Hui Cui 002; Tiangang Zhang; Toshiya Nakaguchi (IEEE J. Biomed. Health Informatics, 2022)

Graph Triple-Attention Network for Disease-Related LncRNA Prediction. - Ping Xuan; Liyun Zhan; Hui Cui 002; Tiangang Zhang; Toshiya Nakaguchi; Weixiong Zhang (IEEE J. Biomed. Health Informatics, 2022)

Semantic Meta-Path Enhanced Global and Local Topology Learning for lncRNA-Disease Association Prediction. - Ping Xuan; Yue Zhao; Hui Cui 002; Linyun Zhan; Qiangguo Jin; Tiangang Zhang; Toshiya Nakaguchi (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

Multi-scale random walk driven adaptive graph neural network with dual-head neighboring node attention for CT segmentation. - Ping Xuan; Xixi Wu; Hui Cui 002; Qiangguo Jin; Linlin Wang; Tiangang Zhang; Toshiya Nakaguchi; Henry B. L. Duh (Appl. Soft Comput., 2023)

Specific topology and topological connection sensitivity enhanced graph learning for lncRNA-disease association prediction. - Ping Xuan; Honglei Bai; Hui Cui 002; Xiaowen Zhang; Toshiya Nakaguchi; Tiangang Zhang (Comput. Biol. Medicine, 2023)

Graph Reasoning Method Based on Affinity Identification and Representation Decoupling for Predicting lncRNA-Disease Associations. - Shuai Wang 038; Hui Cui 002; Tiangang Zhang; Peiliang Wu; Toshiya Nakaguchi; Ping Xuan (J. Chem. Inf. Model., 2023)

Evolving graph convolutional network with transformer for CT segmentation. - Hui Cui 002; Qiangguo Jin; Xixi Wu; Linlin Wang; Tiangang Zhang; Toshiya Nakaguchi; Ping Xuan; David Dagan Feng (Appl. Soft Comput., 2024)

Multi-view attribute learning and context relationship encoding enhanced segmentation of lung tumors from CT images. - Ping Xuan; Xiuqiang Chu; Hui Cui 002; Toshiya Nakaguchi; Linlin Wang; Zhiyuan Ning; Zhiyu Ning; Changyang Li; Tiangang Zhang (Comput. Biol. Medicine, 2024)

Gating-Enhanced Hierarchical Structure Learning in Hyperbolic Space and Multi-scale Neighbor Topology Learning in Euclidean Space for Prediction of Microbe-Drug Associations. - Ping Xuan; Chunhong Guan; Sentao Chen; Jing Gu; Xiuju Wang; Toshiya Nakaguchi; Tiangang Zhang (J. Chem. Inf. Model., 2024)

Learning Association Characteristics by Dynamic Hypergraph and Gated Convolution Enhanced Pairwise Attributes for Prediction of Disease-Related lncRNAs. - Ping Xuan; Siyuan Lu; Hui Cui 002; Shuai Wang 038; Toshiya Nakaguchi; Tiangang Zhang (J. Chem. Inf. Model., 2024)

Mask-Guided Target Node Feature Learning and Dynamic Detailed Feature Enhancement for lncRNA-Disease Association Prediction. - Ping Xuan; Wei Wang; Hui Cui 002; Shuai Wang 038; Toshiya Nakaguchi; Tiangang Zhang (J. Chem. Inf. Model., 2024)

Multi-scale topology and position feature learning and relationship-aware graph reasoning for prediction of drug-related microbes. - Ping Xuan; Jing Gu; Hui Cui 002; Shuai Wang 038; Toshiya Nakaguchi; Cheng Liu; Tiangang Zhang (Bioinform., 2024)

Meta-Path Semantic and Global-Local Representation Learning Enhanced Graph Convolutional Model for Disease-Related miRNA Prediction. - Ping Xuan; Xiuju Wang; Hui Cui 002; Xiangfeng Meng; Toshiya Nakaguchi; Tiangang Zhang (IEEE J. Biomed. Health Informatics, 2024)

Interactive multi-hypergraph inferring and channel-enhanced and attribute-enhanced learning for drug-related side effect prediction. - Ping Xuan; Shien Wu; Hui Cui 002; Peiru Li; Toshiya Nakaguchi; Tiangang Zhang (Comput. Biol. Medicine, 2025)

KNDM: A Knowledge Graph Transformer and Node Category Sensitive Contrastive Learning Model for Drug and Microbe Association Prediction. - Dongliang Chen; Tiangang Zhang; Hui Cui 002; Jing Gu; Ping Xuan (J. Chem. Inf. Model., 2025)

Neighborhood Topology-Aware Knowledge Graph Learning and Microbial Preference Inferring for Drug-Microbe Association Prediction. - Jing Gu; Tiangang Zhang; Yihang Gao; Sentao Chen; Yuxin Zhang; Hui Cui 002; Ping Xuan (J. Chem. Inf. Model., 2025)

Multi-Knowledge Graph and Multi-View Entity Feature Learning for Predicting Drug-Related Side Effects. - Ping Xuan; Tianhong Cheng; Hui Cui 002; Jing Gu; Qiangguo Jin; Tiangang Zhang (J. Chem. Inf. Model., 2025)

Subgraph Topology and Dynamic Graph Topology Enhanced Graph Learning and Pairwise Feature Context Relationship Integration for Predicting Disease-Related miRNAs. - Ping Xuan; Xiaoying Qi; Sentao Chen; Jing Gu; Xiuju Wang; Hui Cui 002; Jun Lu; Tiangang Zhang (J. Chem. Inf. Model., 2025)