176 related articles for article (PubMed ID: 30840454)
1. RFSMMA: A New Computational Model to Identify and Prioritize Potential Small Molecule-MiRNA Associations.
Wang CC; Chen X; Qu J; Sun YZ; Li JQ
J Chem Inf Model; 2019 Apr; 59(4):1668-1679. PubMed ID: 30840454
[TBL] [Abstract][Full Text] [Related]
2. Prediction of Small Molecule-MicroRNA Associations by Sparse Learning and Heterogeneous Graph Inference.
Yin J; Chen X; Wang CC; Zhao Y; Sun YZ
Mol Pharm; 2019 Jul; 16(7):3157-3166. PubMed ID: 31136190
[TBL] [Abstract][Full Text] [Related]
3. A Unified Framework for the Prediction of Small Molecule-MicroRNA Association Based on Cross-Layer Dependency Inference on Multilayered Networks.
Wang CC; Chen X
J Chem Inf Model; 2019 Dec; 59(12):5281-5293. PubMed ID: 31765567
[TBL] [Abstract][Full Text] [Related]
4. Ensemble of kernel ridge regression-based small molecule-miRNA association prediction in human disease.
Wang CC; Zhu CC; Chen X
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34676393
[TBL] [Abstract][Full Text] [Related]
5. Neighborhood-based inference and restricted Boltzmann machine for small molecule-miRNA associations prediction.
Qu J; Song Z; Cheng X; Jiang Z; Zhou J
PeerJ; 2023; 11():e15889. PubMed ID: 37641598
[TBL] [Abstract][Full Text] [Related]
6. SNMFSMMA: using symmetric nonnegative matrix factorization and Kronecker regularized least squares to predict potential small molecule-microRNA association.
Zhao Y; Chen X; Yin J; Qu J
RNA Biol; 2020 Feb; 17(2):281-291. PubMed ID: 31739716
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. In Silico Prediction of Small Molecule-miRNA Associations Based on the HeteSim Algorithm.
Qu J; Chen X; Sun YZ; Zhao Y; Cai SB; Ming Z; You ZH; Li JQ
Mol Ther Nucleic Acids; 2019 Mar; 14():274-286. PubMed ID: 30654189
[TBL] [Abstract][Full Text] [Related]
9. Predicting potential small molecule-miRNA associations based on bounded nuclear norm regularization.
Chen X; Zhou C; Wang CC; Zhao Y
Brief Bioinform; 2021 Nov; 22(6):. PubMed ID: 34404088
[TBL] [Abstract][Full Text] [Related]
10. Inferring potential small molecule-miRNA association based on triple layer heterogeneous network.
Qu J; Chen X; Sun YZ; Li JQ; Ming Z
J Cheminform; 2018 Jun; 10(1):30. PubMed ID: 29943160
[TBL] [Abstract][Full Text] [Related]
11. Dual-Network Collaborative Matrix Factorization for predicting small molecule-miRNA associations.
Wang SH; Wang CC; Huang L; Miao LY; Chen X
Brief Bioinform; 2022 Jan; 23(1):. PubMed ID: 34864865
[TBL] [Abstract][Full Text] [Related]
12. Prediction of Potential Small Molecule-Associated MicroRNAs Using Graphlet Interaction.
Guan NN; Sun YZ; Ming Z; Li JQ; Chen X
Front Pharmacol; 2018; 9():1152. PubMed ID: 30374302
[TBL] [Abstract][Full Text] [Related]
13. Identifying SM-miRNA associations based on layer attention graph convolutional network and matrix decomposition.
Ni J; Cheng X; Ni T; Liang J
Front Mol Biosci; 2022; 9():1009099. PubMed ID: 36504714
[TBL] [Abstract][Full Text] [Related]
14. Novel Human miRNA-Disease Association Inference Based on Random Forest.
Chen X; Wang CC; Yin J; You ZH
Mol Ther Nucleic Acids; 2018 Dec; 13():568-579. PubMed ID: 30439645
[TBL] [Abstract][Full Text] [Related]
15. ELLPMDA: Ensemble learning and link prediction for miRNA-disease association prediction.
Chen X; Zhou Z; Zhao Y
RNA Biol; 2018; 15(6):807-818. PubMed ID: 29619882
[TBL] [Abstract][Full Text] [Related]
16. PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction.
You ZH; Huang ZA; Zhu Z; Yan GY; Li ZW; Wen Z; Chen X
PLoS Comput Biol; 2017 Mar; 13(3):e1005455. PubMed ID: 28339468
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. A novel computational model based on super-disease and miRNA for potential miRNA-disease association prediction.
Chen X; Jiang ZC; Xie D; Huang DS; Zhao Q; Yan GY; You ZH
Mol Biosyst; 2017 May; 13(6):1202-1212. PubMed ID: 28470244
[TBL] [Abstract][Full Text] [Related]
19. SSCMDA: spy and super cluster strategy for MiRNA-disease association prediction.
Zhao Q; Xie D; Liu H; Wang F; Yan GY; Chen X
Oncotarget; 2018 Jan; 9(2):1826-1842. PubMed ID: 29416734
[TBL] [Abstract][Full Text] [Related]
20. Prediction of potential small molecule-miRNA associations based on heterogeneous network representation learning.
Li J; Lin H; Wang Y; Li Z; Wu B
Front Genet; 2022; 13():1079053. PubMed ID: 36531225
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]