347 related articles for article (PubMed ID: 34890410)
1. GCAEMDA: Predicting miRNA-disease associations via graph convolutional autoencoder.
Li L; Wang YT; Ji CM; Zheng CH; Ni JC; Su YS
PLoS Comput Biol; 2021 Dec; 17(12):e1009655. PubMed ID: 34890410
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. Variational graph auto-encoders for miRNA-disease association prediction.
Ding Y; Tian LP; Lei X; Liao B; Wu FX
Methods; 2021 Aug; 192():25-34. PubMed ID: 32798654
[TBL] [Abstract][Full Text] [Related]
4. Predicting miRNA-Disease Association Based on Improved Graph Regression.
Li L; Gao Z; Zheng CH; Qi R; Wang YT; Ni JC
IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(6):3604-3613. PubMed ID: 34757912
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. 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]
7. 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]
8. SFGAE: a self-feature-based graph autoencoder model for miRNA-disease associations prediction.
Ma M; Na S; Zhang X; Chen C; Xu J
Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 36037084
[TBL] [Abstract][Full Text] [Related]
9. DNRLMF-MDA:Predicting microRNA-Disease Associations Based on Similarities of microRNAs and Diseases.
Yan C; Wang J; Ni P; Lan W; Wu FX; Pan Y
IEEE/ACM Trans Comput Biol Bioinform; 2019; 16(1):233-243. PubMed ID: 29990253
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. A graph auto-encoder model for miRNA-disease associations prediction.
Li Z; Li J; Nie R; You ZH; Bao W
Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 34293850
[TBL] [Abstract][Full Text] [Related]
12. Variational gated autoencoder-based feature extraction model for inferring disease-miRNA associations based on multiview features.
Guo Y; Zhou D; Ruan X; Cao J
Neural Netw; 2023 Aug; 165():491-505. PubMed ID: 37336034
[TBL] [Abstract][Full Text] [Related]
13. Predicting MiRNA-disease associations by multiple meta-paths fusion graph embedding model.
Zhang L; Liu B; Li Z; Zhu X; Liang Z; An J
BMC Bioinformatics; 2020 Oct; 21(1):470. PubMed ID: 33087064
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. SGAEMDA: Predicting miRNA-Disease Associations Based on Stacked Graph Autoencoder.
Wang S; Lin B; Zhang Y; Qiao S; Wang F; Wu W; Ren C
Cells; 2022 Dec; 11(24):. PubMed ID: 36552748
[TBL] [Abstract][Full Text] [Related]
16. LDAPred: A Method Based on Information Flow Propagation and a Convolutional Neural Network for the Prediction of Disease-Associated lncRNAs.
Xuan P; Jia L; Zhang T; Sheng N; Li X; Li J
Int J Mol Sci; 2019 Sep; 20(18):. PubMed ID: 31510011
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. NEMPD: a network embedding-based method for predicting miRNA-disease associations by preserving behavior and attribute information.
Ji BY; You ZH; Chen ZH; Wong L; Yi HC
BMC Bioinformatics; 2020 Sep; 21(1):401. PubMed ID: 32912137
[TBL] [Abstract][Full Text] [Related]
19. MDHGI: Matrix Decomposition and Heterogeneous Graph Inference for miRNA-disease association prediction.
Chen X; Yin J; Qu J; Huang L
PLoS Comput Biol; 2018 Aug; 14(8):e1006418. PubMed ID: 30142158
[TBL] [Abstract][Full Text] [Related]
20. Graph embedding ensemble methods based on the heterogeneous network for lncRNA-miRNA interaction prediction.
Zhao C; Qiu Y; Zhou S; Liu S; Zhang W; Niu Y
BMC Genomics; 2020 Dec; 21(Suppl 13):867. PubMed ID: 33334307
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
