These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

419 related articles for article (PubMed ID: 28177900)

  • 1. MCMDA: Matrix completion for MiRNA-disease association prediction.
    Li JQ; Rong ZH; Chen X; Yan GY; You ZH
    Oncotarget; 2017 Mar; 8(13):21187-21199. PubMed ID: 28177900
    [TBL] [Abstract][Full Text] [Related]  

  • 2. In silico prediction of potential miRNA-disease association using an integrative bioinformatics approach based on kernel fusion.
    Guan NN; Wang CC; Zhang L; Huang L; Li JQ; Piao X
    J Cell Mol Med; 2020 Jan; 24(1):573-587. PubMed ID: 31747722
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Dual Laplacian regularized matrix completion for microRNA-disease associations prediction.
    Tang C; Zhou H; Zheng X; Zhang Y; Sha X
    RNA Biol; 2019 May; 16(5):601-611. PubMed ID: 30676207
    [TBL] [Abstract][Full Text] [Related]  

  • 4. NARRMDA: negative-aware and rating-based recommendation algorithm for miRNA-disease association prediction.
    Peng L; Chen Y; Ma N; Chen X
    Mol Biosyst; 2017 Nov; 13(12):2650-2659. PubMed ID: 29053164
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. 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]  

  • 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. 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]  

  • 9. WBSMDA: Within and Between Score for MiRNA-Disease Association prediction.
    Chen X; Yan CC; Zhang X; You ZH; Deng L; Liu Y; Zhang Y; Dai Q
    Sci Rep; 2016 Feb; 6():21106. PubMed ID: 26880032
    [TBL] [Abstract][Full Text] [Related]  

  • 10. EGBMMDA: Extreme Gradient Boosting Machine for MiRNA-Disease Association prediction.
    Chen X; Huang L; Xie D; Zhao Q
    Cell Death Dis; 2018 Jan; 9(1):3. PubMed ID: 29305594
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. NDAMDA: Network distance analysis for MiRNA-disease association prediction.
    Chen X; Wang LY; Huang L
    J Cell Mol Med; 2018 May; 22(5):2884-2895. PubMed ID: 29532987
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. 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]  

  • 15. 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]  

  • 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. Ensemble of decision tree reveals potential miRNA-disease associations.
    Chen X; Zhu CC; Yin J
    PLoS Comput Biol; 2019 Jul; 15(7):e1007209. PubMed ID: 31329575
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. 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]  

  • 20. 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]  

    [Next]    [New Search]
    of 21.