283 related articles for article (PubMed ID: 35428965)
1. DNRLCNN: A CNN Framework for Identifying MiRNA-Disease Associations Using Latent Feature Matrix Extraction with Positive Samples.
Zhong J; Zhou W; Kang J; Fang Z; Xie M; Xiao Q; Peng W
Interdiscip Sci; 2022 Jun; 14(2):607-622. PubMed ID: 35428965
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. An improved random forest-based computational model for predicting novel miRNA-disease associations.
Yao D; Zhan X; Kwoh CK
BMC Bioinformatics; 2019 Dec; 20(1):624. PubMed ID: 31795954
[TBL] [Abstract][Full Text] [Related]
4. Predicting MiRNA-Disease Association by Latent Feature Extraction with Positive Samples.
Che K; Guo M; Wang C; Liu X; Chen X
Genes (Basel); 2019 Jan; 10(2):. PubMed ID: 30682853
[TBL] [Abstract][Full Text] [Related]
5. A structural deep network embedding model for predicting associations between miRNA and disease based on molecular association network.
Li HY; Chen HY; Wang L; Song SJ; You ZH; Yan X; Yu JQ
Sci Rep; 2021 Jun; 11(1):12640. PubMed ID: 34135401
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. 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]
8. An integrated framework for the identification of potential miRNA-disease association based on novel negative samples extraction strategy.
Wang CC; Chen X; Yin J; Qu J
RNA Biol; 2019 Mar; 16(3):257-269. PubMed ID: 30646823
[TBL] [Abstract][Full Text] [Related]
9. MicroRNA-disease association prediction by matrix tri-factorization.
Li H; Guo Y; Cai M; Li L
BMC Genomics; 2020 Nov; 21(Suppl 10):617. PubMed ID: 33208088
[TBL] [Abstract][Full Text] [Related]
10. MDA-GCNFTG: identifying miRNA-disease associations based on graph convolutional networks via graph sampling through the feature and topology graph.
Chu Y; Wang X; Dai Q; Wang Y; Wang Q; Peng S; Wei X; Qiu J; Salahub DR; Xiong Y; Wei DQ
Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34009265
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. 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]
13. WBNPMD: weighted bipartite network projection for microRNA-disease association prediction.
Xie G; Fan Z; Sun Y; Wu C; Ma L
J Transl Med; 2019 Sep; 17(1):322. PubMed ID: 31547811
[TBL] [Abstract][Full Text] [Related]
14. PMDAGS: Predicting miRNA-Disease Associations With Graph Nonlinear Diffusion Convolution Network and Similarities.
Yan C; Duan G
IEEE/ACM Trans Comput Biol Bioinform; 2024; 21(3):394-404. PubMed ID: 38358864
[TBL] [Abstract][Full Text] [Related]
15. Predicting miRNA-disease associations based on lncRNA-miRNA interactions and graph convolution networks.
Wang W; Chen H
Brief Bioinform; 2023 Jan; 24(1):. PubMed ID: 36526276
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Predicting miRNA-Disease Associations Through Deep Autoencoder With Multiple Kernel Learning.
Zhou F; Yin MM; Jiao CN; Zhao JX; Zheng CH; Liu JX
IEEE Trans Neural Netw Learn Syst; 2023 Sep; 34(9):5570-5579. PubMed ID: 34860656
[TBL] [Abstract][Full Text] [Related]
18. Computational method using heterogeneous graph convolutional network model combined with reinforcement layer for MiRNA-disease association prediction.
Huang D; An J; Zhang L; Liu B
BMC Bioinformatics; 2022 Jul; 23(1):299. PubMed ID: 35879658
[TBL] [Abstract][Full Text] [Related]
19. A Method Based On Dual-Network Information Fusion to Predict MiRNA-Disease Associations.
Zhou F; Yin MM; Zhao JX; Shang J; Liu JX
IEEE/ACM Trans Comput Biol Bioinform; 2023; 20(1):52-60. PubMed ID: 34882558
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]