232 related articles for article (PubMed ID: 29763707)
1. Predicting microRNA-disease associations using label propagation based on linear neighborhood similarity.
Li G; Luo J; Xiao Q; Liang C; Ding P
J Biomed Inform; 2018 Jun; 82():169-177. PubMed ID: 29763707
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. 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]
5. MiRNA-disease interaction prediction based on kernel neighborhood similarity and multi-network bidirectional propagation.
Ma Y; He T; Ge L; Zhang C; Jiang X
BMC Med Genomics; 2019 Dec; 12(Suppl 10):185. PubMed ID: 31865912
[TBL] [Abstract][Full Text] [Related]
6. A Fast Linear Neighborhood Similarity-Based Network Link Inference Method to Predict MicroRNA-Disease Associations.
Zhang W; Li Z; Guo W; Yang W; Huang F
IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(2):405-415. PubMed ID: 31369383
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. NTSMDA: prediction of miRNA-disease associations by integrating network topological similarity.
Sun D; Li A; Feng H; Wang M
Mol Biosyst; 2016 Jun; 12(7):2224-32. PubMed ID: 27153230
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. Improved Prediction of miRNA-Disease Associations Based on Matrix Completion with Network Regularization.
Ha J; Park C; Park C; Park S
Cells; 2020 Apr; 9(4):. PubMed ID: 32260218
[TBL] [Abstract][Full Text] [Related]
11. A Novel Neighborhood-Based Computational Model for Potential MiRNA-Disease Association Prediction.
Liu Y; Li X; Feng X; Wang L
Comput Math Methods Med; 2019; 2019():5145646. PubMed ID: 30800172
[TBL] [Abstract][Full Text] [Related]
12. LncRNA-miRNA interaction prediction through sequence-derived linear neighborhood propagation method with information combination.
Zhang W; Tang G; Zhou S; Niu Y
BMC Genomics; 2019 Dec; 20(Suppl 11):946. PubMed ID: 31856716
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Prediction of microRNA-disease associations based on distance correlation set.
Zhao H; Kuang L; Wang L; Ping P; Xuan Z; Pei T; Wu Z
BMC Bioinformatics; 2018 Apr; 19(1):141. PubMed ID: 29665774
[TBL] [Abstract][Full Text] [Related]
15. Prediction of Disease-related microRNAs through Integrating Attributes of microRNA Nodes and Multiple Kinds of Connecting Edges.
Xuan P; Li L; Zhang T; Zhang Y; Song Y
Molecules; 2019 Aug; 24(17):. PubMed ID: 31455026
[TBL] [Abstract][Full Text] [Related]
16. GIMDA: Graphlet interaction-based MiRNA-disease association prediction.
Chen X; Guan NN; Li JQ; Yan GY
J Cell Mol Med; 2018 Mar; 22(3):1548-1561. PubMed ID: 29272076
[TBL] [Abstract][Full Text] [Related]
17. Integration of Multiple Genomic and Phenotype Data to Infer Novel miRNA-Disease Associations.
Shi H; Zhang G; Zhou M; Cheng L; Yang H; Wang J; Sun J; Wang Z
PLoS One; 2016; 11(2):e0148521. PubMed ID: 26849207
[TBL] [Abstract][Full Text] [Related]
18. LMTRDA: Using logistic model tree to predict MiRNA-disease associations by fusing multi-source information of sequences and similarities.
Wang L; You ZH; Chen X; Li YM; Dong YN; Li LP; Zheng K
PLoS Comput Biol; 2019 Mar; 15(3):e1006865. PubMed ID: 30917115
[TBL] [Abstract][Full Text] [Related]
19. Prediction of potential disease-associated microRNAs using structural perturbation method.
Zeng X; Liu L; Lü L; Zou Q
Bioinformatics; 2018 Jul; 34(14):2425-2432. PubMed ID: 29490018
[TBL] [Abstract][Full Text] [Related]
20. Identifying human microRNA-disease associations by a new diffusion-based method.
Liao B; Ding S; Chen H; Li Z; Cai L
J Bioinform Comput Biol; 2015 Aug; 13(4):1550014. PubMed ID: 26004789
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]