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 *

210 related articles for article (PubMed ID: 34020550)

  • 1. Deep-belief network for predicting potential miRNA-disease associations.
    Chen X; Li TH; Zhao Y; Wang CC; Zhu CC
    Brief Bioinform; 2021 May; 22(3):. PubMed ID: 34020550
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Prediction of potential miRNA-disease associations based on stacked autoencoder.
    Wang CC; Li TH; Huang L; Chen X
    Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35176761
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. 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]  

  • 5. Prediction of Potential miRNA-Disease Associations Through a Novel Unsupervised Deep Learning Framework with Variational Autoencoder.
    Zhang L; Chen X; Yin J
    Cells; 2019 Sep; 8(9):. PubMed ID: 31489920
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Computational method using heterogeneous graph convolutional network model combined with reinforcement layer for MiRNA-disease association prediction.
    Huang D; An J; Zhang L; Liu B
    BMC Bioinformatics; 2022 Jul; 23(1):299. PubMed ID: 35879658
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. SGANRDA: semi-supervised generative adversarial networks for predicting circRNA-disease associations.
    Wang L; Yan X; You ZH; Zhou X; Li HY; Huang YA
    Brief Bioinform; 2021 Sep; 22(5):. PubMed ID: 33734296
    [TBL] [Abstract][Full Text] [Related]  

  • 10. NCMCMDA: miRNA-disease association prediction through neighborhood constraint matrix completion.
    Chen X; Sun LG; Zhao Y
    Brief Bioinform; 2021 Jan; 22(1):485-496. PubMed ID: 31927572
    [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. 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]  

  • 13. Predicting miRNA-disease association from heterogeneous information network with GraRep embedding model.
    Ji BY; You ZH; Cheng L; Zhou JR; Alghazzawi D; Li LP
    Sci Rep; 2020 Apr; 10(1):6658. PubMed ID: 32313121
    [TBL] [Abstract][Full Text] [Related]  

  • 14. KATZNCP: a miRNA-disease association prediction model integrating KATZ algorithm and network consistency projection.
    Chen M; Deng Y; Li Z; Ye Y; He Z
    BMC Bioinformatics; 2023 Jun; 24(1):229. PubMed ID: 37268893
    [TBL] [Abstract][Full Text] [Related]  

  • 15. LRSSLMDA: Laplacian Regularized Sparse Subspace Learning for MiRNA-Disease Association prediction.
    Chen X; Huang L
    PLoS Comput Biol; 2017 Dec; 13(12):e1005912. PubMed ID: 29253885
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. Prediction of miRNA-disease associations by neural network-based deep matrix factorization.
    Qu Q; Chen X; Ning B; Zhang X; Nie H; Zeng L; Chen H; Fu X
    Methods; 2023 Apr; 212():1-9. PubMed ID: 36813017
    [TBL] [Abstract][Full Text] [Related]  

  • 18. 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]  

  • 19. 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]  

  • 20. 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]  

    [Next]    [New Search]
    of 11.