BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

334 related articles for article (PubMed ID: 29053164)

  • 1. 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]  

  • 2. 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]  

  • 3. 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]  

  • 4. 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]  

  • 5. 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]  

  • 6. 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]  

  • 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. HAMDA: Hybrid Approach for MiRNA-Disease Association prediction.
    Chen X; Niu YW; Wang GH; Yan GY
    J Biomed Inform; 2017 Dec; 76():50-58. PubMed ID: 29097278
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. 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]  

  • 12. HNMDA: heterogeneous network-based miRNA-disease association prediction.
    Peng LH; Sun CN; Guan NN; Li JQ; Chen X
    Mol Genet Genomics; 2018 Aug; 293(4):983-995. PubMed ID: 29687157
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. 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]  

  • 15. Predicting miRNA-disease association based on inductive matrix completion.
    Chen X; Wang L; Qu J; Guan NN; Li JQ
    Bioinformatics; 2018 Dec; 34(24):4256-4265. PubMed ID: 29939227
    [TBL] [Abstract][Full Text] [Related]  

  • 16. HGIMDA: Heterogeneous graph inference for miRNA-disease association prediction.
    Chen X; Yan CC; Zhang X; You ZH; Huang YA; Yan GY
    Oncotarget; 2016 Oct; 7(40):65257-65269. PubMed ID: 27533456
    [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. RKNNMDA: Ranking-based KNN for MiRNA-Disease Association prediction.
    Chen X; Wu QF; Yan GY
    RNA Biol; 2017 Jul; 14(7):952-962. PubMed ID: 28421868
    [TBL] [Abstract][Full Text] [Related]  

  • 19. MKRMDA: multiple kernel learning-based Kronecker regularized least squares for MiRNA-disease association prediction.
    Chen X; Niu YW; Wang GH; Yan GY
    J Transl Med; 2017 Dec; 15(1):251. PubMed ID: 29233191
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 17.