177 related articles for article (PubMed ID: 38384286)
1. Prediction of drug-disease associations based on reinforcement symmetric metric learning and graph convolution network.
Luo H; Zhu C; Wang J; Zhang G; Luo J; Yan C
Front Pharmacol; 2024; 15():1337764. PubMed ID: 38384286
[TBL] [Abstract][Full Text] [Related]
2. RLFDDA: a meta-path based graph representation learning model for drug-disease association prediction.
Zhang ML; Zhao BW; Su XR; He YZ; Yang Y; Hu L
BMC Bioinformatics; 2022 Dec; 23(1):516. PubMed ID: 36456957
[TBL] [Abstract][Full Text] [Related]
3. Fusing graph transformer with multi-aggregate GCN for enhanced drug-disease associations prediction.
He S; Yun L; Yi H
BMC Bioinformatics; 2024 Feb; 25(1):79. PubMed ID: 38378479
[TBL] [Abstract][Full Text] [Related]
4. Partner-Specific Drug Repositioning Approach Based on Graph Convolutional Network.
Sun X; Wang B; Zhang J; Li M
IEEE J Biomed Health Inform; 2022 Nov; 26(11):5757-5765. PubMed ID: 35921345
[TBL] [Abstract][Full Text] [Related]
5. Drug repositioning based on heterogeneous networks and variational graph autoencoders.
Lei S; Lei X; Liu L
Front Pharmacol; 2022; 13():1056605. PubMed ID: 36618933
[TBL] [Abstract][Full Text] [Related]
6. GCNGAT: Drug-disease association prediction based on graph convolution neural network and graph attention network.
Yang R; Fu Y; Zhang Q; Zhang L
Artif Intell Med; 2024 Apr; 150():102805. PubMed ID: 38553169
[TBL] [Abstract][Full Text] [Related]
7. Drug repositioning based on the heterogeneous information fusion graph convolutional network.
Cai L; Lu C; Xu J; Meng Y; Wang P; Fu X; Zeng X; Su Y
Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34378011
[TBL] [Abstract][Full Text] [Related]
8. MGRL: Predicting Drug-Disease Associations Based on Multi-Graph Representation Learning.
Zhao BW; You ZH; Wong L; Zhang P; Li HY; Wang L
Front Genet; 2021; 12():657182. PubMed ID: 34054920
[TBL] [Abstract][Full Text] [Related]
9. DTI-HETA: prediction of drug-target interactions based on GCN and GAT on heterogeneous graph.
Shao K; Zhang Y; Wen Y; Zhang Z; He S; Bo X
Brief Bioinform; 2022 May; 23(3):. PubMed ID: 35380622
[TBL] [Abstract][Full Text] [Related]
10. HINGRL: predicting drug-disease associations with graph representation learning on heterogeneous information networks.
Zhao BW; Hu L; You ZH; Wang L; Su XR
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34891172
[TBL] [Abstract][Full Text] [Related]
11. A Convolutional Neural Network and Graph Convolutional Network Based Framework for Classification of Breast Histopathological Images.
Gao Z; Lu Z; Wang J; Ying S; Shi J
IEEE J Biomed Health Inform; 2022 Jul; 26(7):3163-3173. PubMed ID: 35196251
[TBL] [Abstract][Full Text] [Related]
12. A Biological Feature and Heterogeneous Network Representation Learning-Based Framework for Drug-Target Interaction Prediction.
Liu L; Zhang Q; Wei Y; Zhao Q; Liao B
Molecules; 2023 Sep; 28(18):. PubMed ID: 37764321
[TBL] [Abstract][Full Text] [Related]
13. MAMF-GCN: Multi-scale adaptive multi-channel fusion deep graph convolutional network for predicting mental disorder.
Pan J; Lin H; Dong Y; Wang Y; Ji Y
Comput Biol Med; 2022 Sep; 148():105823. PubMed ID: 35872410
[TBL] [Abstract][Full Text] [Related]
14. Hierarchical Negative Sampling Based Graph Contrastive Learning Approach for Drug-Disease Association Prediction.
Wang Y; Song J; Dai Q; Duan X
IEEE J Biomed Health Inform; 2024 May; 28(5):3146-3157. PubMed ID: 38294927
[TBL] [Abstract][Full Text] [Related]
15. Identifying drug-target interactions based on graph convolutional network and deep neural network.
Zhao T; Hu Y; Valsdottir LR; Zang T; Peng J
Brief Bioinform; 2021 Mar; 22(2):2141-2150. PubMed ID: 32367110
[TBL] [Abstract][Full Text] [Related]
16. Predicting CircRNA disease associations using novel node classification and link prediction models on Graph Convolutional Networks.
Bamunu Mudiyanselage T; Lei X; Senanayake N; Zhang Y; Pan Y
Methods; 2022 Feb; 198():32-44. PubMed ID: 34748953
[TBL] [Abstract][Full Text] [Related]
17. An effective multi-task learning framework for drug repurposing based on graph representation learning.
Ye S; Zhao W; Shen X; Jiang X; He T
Methods; 2023 Oct; 218():48-56. PubMed ID: 37516260
[TBL] [Abstract][Full Text] [Related]
18. Hi-GCN: A hierarchical graph convolution network for graph embedding learning of brain network and brain disorders prediction.
Jiang H; Cao P; Xu M; Yang J; Zaiane O
Comput Biol Med; 2020 Dec; 127():104096. PubMed ID: 33166800
[TBL] [Abstract][Full Text] [Related]
19. DAHNGC: A Graph Convolution Model for Drug-Disease Association Prediction by Using Heterogeneous Network.
Zhong J; Cui P; Zhu Y; Xiao Q; Qu Z
J Comput Biol; 2023 Sep; 30(9):1019-1033. PubMed ID: 37702623
[TBL] [Abstract][Full Text] [Related]
20. A Novel Drug Repositioning Approach Based on Collaborative Metric Learning.
Luo H; Wang J; Yan C; Li M; Wu FX; Pan Y
IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(2):463-471. PubMed ID: 31283509
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]