338 related articles for article (PubMed ID: 37531860)
1. Specific topology and topological connection sensitivity enhanced graph learning for lncRNA-disease association prediction.
Xuan P; Bai H; Cui H; Zhang X; Nakaguchi T; Zhang T
Comput Biol Med; 2023 Sep; 164():107265. PubMed ID: 37531860
[TBL] [Abstract][Full Text] [Related]
2. Semantic Meta-Path Enhanced Global and Local Topology Learning for lncRNA-Disease Association Prediction.
Xuan P; Zhao Y; Cui H; Zhan L; Jin Q; Zhang T; Nakaguchi T
IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(2):1480-1491. PubMed ID: 36173783
[TBL] [Abstract][Full Text] [Related]
3. Attentional multi-level representation encoding based on convolutional and variance autoencoders for lncRNA-disease association prediction.
Sheng N; Cui H; Zhang T; Xuan P
Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32444875
[TBL] [Abstract][Full Text] [Related]
4. Learning global dependencies and multi-semantics within heterogeneous graph for predicting disease-related lncRNAs.
Xuan P; Wang S; Cui H; Zhao Y; Zhang T; Wu P
Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 36088549
[TBL] [Abstract][Full Text] [Related]
5. Fully connected autoencoder and convolutional neural network with attention-based method for inferring disease-related lncRNAs.
Xuan P; Gong Z; Cui H; Li B; Zhang T
Brief Bioinform; 2022 May; 23(3):. PubMed ID: 35362511
[TBL] [Abstract][Full Text] [Related]
6. multi-type neighbors enhanced global topology and pairwise attribute learning for drug-protein interaction prediction.
Xuan P; Zhang X; Zhang Y; Hu K; Nakaguchi T; Zhang T
Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 35514190
[TBL] [Abstract][Full Text] [Related]
7. Graph Convolutional Network and Convolutional Neural Network Based Method for Predicting lncRNA-Disease Associations.
Xuan P; Pan S; Zhang T; Liu Y; Sun H
Cells; 2019 Aug; 8(9):. PubMed ID: 31480350
[TBL] [Abstract][Full Text] [Related]
8. Integration of pairwise neighbor topologies and miRNA family and cluster attributes for miRNA-disease association prediction.
Xuan P; Wang D; Cui H; Zhang T; Nakaguchi T
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34634106
[TBL] [Abstract][Full Text] [Related]
9. Graph Triple-Attention Network for Disease-Related LncRNA Prediction.
Xuan P; Zhan L; Cui H; Zhang T; Nakaguchi T; Zhang W
IEEE J Biomed Health Inform; 2022 Jun; 26(6):2839-2849. PubMed ID: 34813484
[TBL] [Abstract][Full Text] [Related]
10. Graph generative and adversarial strategy-enhanced node feature learning and self-calibrated pairwise attribute encoding for prediction of drug-related side effects.
Xuan P; Xu K; Cui H; Nakaguchi T; Zhang T
Front Pharmacol; 2023; 14():1257842. PubMed ID: 37731739
[No Abstract] [Full Text] [Related]
11. CNNDLP: A Method Based on Convolutional Autoencoder and Convolutional Neural Network with Adjacent Edge Attention for Predicting lncRNA-Disease Associations.
Xuan P; Sheng N; Zhang T; Liu Y; Guo Y
Int J Mol Sci; 2019 Aug; 20(17):. PubMed ID: 31480319
[TBL] [Abstract][Full Text] [Related]
12. GVDTI: graph convolutional and variational autoencoders with attribute-level attention for drug-protein interaction prediction.
Xuan P; Fan M; Cui H; Zhang T; Nakaguchi T
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34718408
[TBL] [Abstract][Full Text] [Related]
13. Integrating specific and common topologies of heterogeneous graphs and pairwise attributes for drug-related side effect prediction.
Xuan P; Wang M; Liu Y; Wang D; Zhang T; Nakaguchi T
Brief Bioinform; 2022 May; 23(3):. PubMed ID: 35470853
[TBL] [Abstract][Full Text] [Related]
14. Integration of Neighbor Topologies Based on Meta-Paths and Node Attributes for Predicting Drug-Related Diseases.
Xuan P; Lu Z; Zhang T; Liu Y; Nakaguchi T
Int J Mol Sci; 2022 Mar; 23(7):. PubMed ID: 35409235
[TBL] [Abstract][Full Text] [Related]
15. Learning Association Characteristics by Dynamic Hypergraph and Gated Convolution Enhanced Pairwise Attributes for Prediction of Disease-Related lncRNAs.
Xuan P; Lu S; Cui H; Wang S; Nakaguchi T; Zhang T
J Chem Inf Model; 2024 Apr; 64(8):3569-3578. PubMed ID: 38523267
[TBL] [Abstract][Full Text] [Related]
16. Learning multi-scale heterogenous network topologies and various pairwise attributes for drug-disease association prediction.
Zhang H; Cui H; Zhang T; Cao Y; Xuan P
Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35136910
[TBL] [Abstract][Full Text] [Related]
17. ALDPI: adaptively learning importance of multi-scale topologies and multi-modality similarities for drug-protein interaction prediction.
Hu K; Cui H; Zhang T; Sun C; Xuan P
Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35108362
[TBL] [Abstract][Full Text] [Related]
18. Learning Multi-Types of Neighbor Node Attributes and Semantics by Heterogeneous Graph Transformer and Multi-View Attention for Drug-Related Side-Effect Prediction.
Xuan P; Li P; Cui H; Wang M; Nakaguchi T; Zhang T
Molecules; 2023 Sep; 28(18):. PubMed ID: 37764319
[TBL] [Abstract][Full Text] [Related]
19. Predicting lncRNA-disease associations using network topological similarity based on deep mining heterogeneous networks.
Zhang H; Liang Y; Peng C; Han S; Du W; Li Y
Math Biosci; 2019 Sep; 315():108229. PubMed ID: 31323239
[TBL] [Abstract][Full Text] [Related]
20. Multi-task prediction-based graph contrastive learning for inferring the relationship among lncRNAs, miRNAs and diseases.
Sheng N; Wang Y; Huang L; Gao L; Cao Y; Xie X; Fu Y
Brief Bioinform; 2023 Sep; 24(5):. PubMed ID: 37529914
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
