244 related articles for article (PubMed ID: 32457435)
41. PDMDA: predicting deep-level miRNA-disease associations with graph neural networks and sequence features.
Yan C; Duan G; Li N; Zhang L; Wu FX; Wang J
Bioinformatics; 2022 Apr; 38(8):2226-2234. PubMed ID: 35150255
[TBL] [Abstract][Full Text] [Related]
42. A heterogeneous label propagation approach to explore the potential associations between miRNA and disease.
Chen X; Zhang DH; You ZH
J Transl Med; 2018 Dec; 16(1):348. PubMed ID: 30537965
[TBL] [Abstract][Full Text] [Related]
43. miRDDCR: a miRNA-based method to comprehensively infer drug-disease causal relationships.
Chen H; Zhang Z; Peng W
Sci Rep; 2017 Nov; 7(1):15921. PubMed ID: 29162848
[TBL] [Abstract][Full Text] [Related]
44. 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]
45. 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]
46. 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]
47. Random walks on mutual microRNA-target gene interaction network improve the prediction of disease-associated microRNAs.
Le DH; Verbeke L; Son LH; Chu DT; Pham VH
BMC Bioinformatics; 2017 Nov; 18(1):479. PubMed ID: 29137601
[TBL] [Abstract][Full Text] [Related]
48. Predicting Disease Related microRNA Based on Similarity and Topology.
Chen Z; Wang X; Gao P; Liu H; Song B
Cells; 2019 Nov; 8(11):. PubMed ID: 31703479
[TBL] [Abstract][Full Text] [Related]
49. ANMDA: anti-noise based computational model for predicting potential miRNA-disease associations.
Chen XJ; Hua XY; Jiang ZR
BMC Bioinformatics; 2021 Jul; 22(1):358. PubMed ID: 34215183
[TBL] [Abstract][Full Text] [Related]
50. 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]
51. 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]
52. A novel method of predicting microRNA-disease associations based on microRNA, disease, gene and environment factor networks.
Peng W; Lan W; Zhong J; Wang J; Pan Y
Methods; 2017 Jul; 124():69-77. PubMed ID: 28576328
[TBL] [Abstract][Full Text] [Related]
53. FCMDAP: using miRNA family and cluster information to improve the prediction accuracy of disease related miRNAs.
Li X; Lin Y; Gu C; Yang J
BMC Syst Biol; 2019 Apr; 13(Suppl 2):26. PubMed ID: 30953512
[TBL] [Abstract][Full Text] [Related]
54. Dual Convolutional Neural Network Based Method for Predicting Disease-Related miRNAs.
Xuan P; Dong Y; Guo Y; Zhang T; Liu Y
Int J Mol Sci; 2018 Nov; 19(12):. PubMed ID: 30477152
[TBL] [Abstract][Full Text] [Related]
55. DRMDA: deep representations-based miRNA-disease association prediction.
Chen X; Gong Y; Zhang DH; You ZH; Li ZW
J Cell Mol Med; 2018 Jan; 22(1):472-485. PubMed ID: 28857494
[TBL] [Abstract][Full Text] [Related]
56. Neural inductive matrix completion with graph convolutional networks for miRNA-disease association prediction.
Li J; Zhang S; Liu T; Ning C; Zhang Z; Zhou W
Bioinformatics; 2020 Apr; 36(8):2538-2546. PubMed ID: 31904845
[TBL] [Abstract][Full Text] [Related]
57. Identification of MiRNA-Disease Associations Based on Information of Multi-Module and Meta-Path.
Li Z; Huang X; Shi Y; Zou X; Li Z; Dai Z
Molecules; 2022 Jul; 27(14):. PubMed ID: 35889314
[TBL] [Abstract][Full Text] [Related]
58. 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]
59. 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]
60. RWRMDA: predicting novel human microRNA-disease associations.
Chen X; Liu MX; Yan GY
Mol Biosyst; 2012 Oct; 8(10):2792-8. PubMed ID: 22875290
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
