196 related articles for article (PubMed ID: 36907654)
1. AMHMDA: attention aware multi-view similarity networks and hypergraph learning for miRNA-disease associations identification.
Ning Q; Zhao Y; Gao J; Chen C; Li X; Li T; Yin M
Brief Bioinform; 2023 Mar; 24(2):. PubMed ID: 36907654
[TBL] [Abstract][Full Text] [Related]
2. HGCLAMIR: Hypergraph contrastive learning with attention mechanism and integrated multi-view representation for predicting miRNA-disease associations.
Ouyang D; Liang Y; Wang J; Li L; Ai N; Feng J; Lu S; Liao S; Liu X; Xie S
PLoS Comput Biol; 2024 Apr; 20(4):e1011927. PubMed ID: 38652712
[TBL] [Abstract][Full Text] [Related]
3. Predicting miRNA-disease associations based on graph random propagation network and attention network.
Zhong T; Li Z; You ZH; Nie R; Zhao H
Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35079767
[TBL] [Abstract][Full Text] [Related]
4. Multi-view Multichannel Attention Graph Convolutional Network for miRNA-disease association prediction.
Tang X; Luo J; Shen C; Lai Z
Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 33963829
[TBL] [Abstract][Full Text] [Related]
5. Predicting miRNA-disease associations based on PPMI and attention network.
Xie X; Wang Y; He K; Sheng N
BMC Bioinformatics; 2023 Mar; 24(1):113. PubMed ID: 36959547
[TBL] [Abstract][Full Text] [Related]
6. Predicting Mirna-Disease Associations Based on Neighbor Selection Graph Attention Networks.
Zhao H; Li Z; You ZH; Nie R; Zhong T
IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(2):1298-1307. PubMed ID: 36067101
[TBL] [Abstract][Full Text] [Related]
7. Adaptive deep propagation graph neural network for predicting miRNA-disease associations.
Hu H; Zhao H; Zhong T; Dong X; Wang L; Han P; Li Z
Brief Funct Genomics; 2023 Nov; 22(5):453-462. PubMed ID: 37078739
[TBL] [Abstract][Full Text] [Related]
8. Predicting miRNA-Disease Associations Based On Multi-View Variational Graph Auto-Encoder With Matrix Factorization.
Ding Y; Lei X; Liao B; Wu FX
IEEE J Biomed Health Inform; 2022 Jan; 26(1):446-457. PubMed ID: 34111017
[TBL] [Abstract][Full Text] [Related]
9. Predicting miRNA-disease associations based on multi-view information fusion.
Xie X; Wang Y; Sheng N; Zhang S; Cao Y; Fu Y
Front Genet; 2022; 13():979815. PubMed ID: 36238163
[TBL] [Abstract][Full Text] [Related]
10. FCGCNMDA: predicting miRNA-disease associations by applying fully connected graph convolutional networks.
Li J; Li Z; Nie R; You Z; Bao W
Mol Genet Genomics; 2020 Sep; 295(5):1197-1209. PubMed ID: 32500265
[TBL] [Abstract][Full Text] [Related]
11. Inferring the Disease-Associated miRNAs Based on Network Representation Learning and Convolutional Neural Networks.
Xuan P; Sun H; Wang X; Zhang T; Pan S
Int J Mol Sci; 2019 Jul; 20(15):. PubMed ID: 31349729
[TBL] [Abstract][Full Text] [Related]
12. Prediction of miRNA-disease associations based on strengthened hypergraph convolutional autoencoder.
Xie GB; Yu JR; Lin ZY; Gu GS; Chen RB; Xu HJ; Liu ZG
Comput Biol Chem; 2024 Feb; 108():107992. PubMed ID: 38056378
[TBL] [Abstract][Full Text] [Related]
13. Predicting miRNA-disease associations via learning multimodal networks and fusing mixed neighborhood information.
Lou Z; Cheng Z; Li H; Teng Z; Liu Y; Tian Z
Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 35524503
[TBL] [Abstract][Full Text] [Related]
14. Predicting miRNA-Disease Associations by Combining Graph and Hypergraph Convolutional Network.
Liang X; Guo M; Jiang L; Fu Y; Zhang P; Chen Y
Interdiscip Sci; 2024 Jan; ():. PubMed ID: 38286905
[TBL] [Abstract][Full Text] [Related]
15. MVNMDA: A Multi-View Network Combing Semantic and Global Features for Predicting miRNA-Disease Association.
Yang C; Wang Z; Zhang S; Li X; Wang X; Liu J; Li R; Zeng S
Molecules; 2023 Dec; 29(1):. PubMed ID: 38202814
[TBL] [Abstract][Full Text] [Related]
16. Predicting miRNA-disease association via graph attention learning and multiplex adaptive modality fusion.
Jin Z; Wang M; Tang C; Zheng X; Zhang W; Sha X; An S
Comput Biol Med; 2024 Feb; 169():107904. PubMed ID: 38181611
[TBL] [Abstract][Full Text] [Related]
17. A Novel Computational Model for Predicting microRNA-Disease Associations Based on Heterogeneous Graph Convolutional Networks.
Li C; Liu H; Hu Q; Que J; Yao J
Cells; 2019 Aug; 8(9):. PubMed ID: 31455028
[TBL] [Abstract][Full Text] [Related]
18. DAEMDA: A Method with Dual-Channel Attention Encoding for miRNA-Disease Association Prediction.
Dong B; Sun W; Xu D; Wang G; Zhang T
Biomolecules; 2023 Oct; 13(10):. PubMed ID: 37892196
[TBL] [Abstract][Full Text] [Related]
19. NMCMDA: neural multicategory MiRNA-disease association prediction.
Wang J; Li J; Yue K; Wang L; Ma Y; Li Q
Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33778850
[TBL] [Abstract][Full Text] [Related]
20. MiRNA-disease association prediction via hypergraph learning based on high-dimensionality features.
Wang YT; Wu QW; Gao Z; Ni JC; Zheng CH
BMC Med Inform Decis Mak; 2021 Apr; 21(Suppl 1):133. PubMed ID: 33882934
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]