These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
196 related articles for article (PubMed ID: 38097930)
1. Predicting potential microbe-disease associations based on auto-encoder and graph convolution network. Lu S; Liang Y; Li L; Miao R; Liao S; Zou Y; Yang C; Ouyang D BMC Bioinformatics; 2023 Dec; 24(1):476. PubMed ID: 38097930 [TBL] [Abstract][Full Text] [Related]
3. Dynamic category-sensitive hypergraph inferring and homo-heterogeneous neighbor feature learning for drug-related microbe prediction. Xuan P; Xu Z; Cui H; Gu J; Liu C; Zhang T; Wu P Bioinformatics; 2024 Sep; 40(9):. PubMed ID: 39292557 [TBL] [Abstract][Full Text] [Related]
4. Microbe-drug association prediction model based on graph convolution and attention networks. Wang B; Wang T; Du X; Li J; Wang J; Wu P Sci Rep; 2024 Sep; 14(1):22327. PubMed ID: 39333143 [TBL] [Abstract][Full Text] [Related]
5. MVGCNMDA: Multi-view Graph Augmentation Convolutional Network for Uncovering Disease-Related Microbes. Hua M; Yu S; Liu T; Yang X; Wang H Interdiscip Sci; 2022 Sep; 14(3):669-682. PubMed ID: 35428964 [TBL] [Abstract][Full Text] [Related]
6. Predicting potential microbe-disease associations based on multi-source features and deep learning. Wang L; Wang Y; Xuan C; Zhang B; Wu H; Gao J Brief Bioinform; 2023 Jul; 24(4):. PubMed ID: 37406190 [TBL] [Abstract][Full Text] [Related]
7. WMGHMDA: a novel weighted meta-graph-based model for predicting human microbe-disease association on heterogeneous information network. Long Y; Luo J BMC Bioinformatics; 2019 Nov; 20(1):541. PubMed ID: 31675979 [TBL] [Abstract][Full Text] [Related]
8. HKFGCN: A novel multiple kernel fusion framework on graph convolutional network to predict microbe-drug associations. Wu Z; Li S; Luo L; Ding P Comput Biol Chem; 2024 Jun; 110():108041. PubMed ID: 38471354 [TBL] [Abstract][Full Text] [Related]
9. GACNNMDA: a computational model for predicting potential human microbe-drug associations based on graph attention network and CNN-based classifier. Ma Q; Tan Y; Wang L BMC Bioinformatics; 2023 Feb; 24(1):35. PubMed ID: 36732704 [TBL] [Abstract][Full Text] [Related]
10. GSAMDA: a computational model for predicting potential microbe-drug associations based on graph attention network and sparse autoencoder. Tan Y; Zou J; Kuang L; Wang X; Zeng B; Zhang Z; Wang L BMC Bioinformatics; 2022 Nov; 23(1):492. PubMed ID: 36401174 [TBL] [Abstract][Full Text] [Related]
11. A novel microbe-drug association prediction model based on graph attention networks and bilayer random forest. Kuang H; Zhang Z; Zeng B; Liu X; Zuo H; Xu X; Wang L BMC Bioinformatics; 2024 Feb; 25(1):78. PubMed ID: 38378437 [TBL] [Abstract][Full Text] [Related]
12. Prediction of microbe-drug associations based on a modified graph attention variational autoencoder and random forest. Wang B; Ma F; Du X; Zhang G; Li J Front Microbiol; 2024; 15():1394302. PubMed ID: 38881658 [TBL] [Abstract][Full Text] [Related]
13. Predicting human microbe-disease associations via graph attention networks with inductive matrix completion. Long Y; Luo J; Zhang Y; Xia Y Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32725163 [TBL] [Abstract][Full Text] [Related]
14. Predicting potential microbe-disease associations with graph attention autoencoder, positive-unlabeled learning, and deep neural network. Peng L; Huang L; Tian G; Wu Y; Li G; Cao J; Wang P; Li Z; Duan L Front Microbiol; 2023; 14():1244527. PubMed ID: 37789848 [TBL] [Abstract][Full Text] [Related]
15. LncRNA-disease association identification using graph auto-encoder and learning to rank. Liang Q; Zhang W; Wu H; Liu B Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36545805 [TBL] [Abstract][Full Text] [Related]
16. GLNNMDA: a multimodal prediction model for microbe-drug associations based on global and local features. Kuang H; Liu X; Tan H; Zhang Z; Zeng B; Wang L Sci Rep; 2024 Sep; 14(1):20847. PubMed ID: 39242712 [TBL] [Abstract][Full Text] [Related]
17. M Wang S; Liu JX; Li F; Wang J; Gao YL IEEE J Biomed Health Inform; 2024 Oct; 28(10):6259-6267. PubMed ID: 39012741 [TBL] [Abstract][Full Text] [Related]
18. Predicting human microbe-drug associations via graph convolutional network with conditional random field. Long Y; Wu M; Kwoh CK; Luo J; Li X Bioinformatics; 2020 Dec; 36(19):4918-4927. PubMed ID: 32597948 [TBL] [Abstract][Full Text] [Related]
19. MCHMDA:Predicting Microbe-Disease Associations Based on Similarities and Low-Rank Matrix Completion. Yan C; Duan G; Wu FX; Pan Y; Wang J IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(2):611-620. PubMed ID: 31295117 [TBL] [Abstract][Full Text] [Related]
20. LCASPMDA: a computational model for predicting potential microbe-drug associations based on learnable graph convolutional attention networks and self-paced iterative sampling ensemble. Yang Z; Wang L; Zhang X; Zeng B; Zhang Z; Liu X Front Microbiol; 2024; 15():1366272. PubMed ID: 38846568 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]