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 *

230 related articles for article (PubMed ID: 37268893)

  • 1. 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]  

  • 2. SCPLPA: An miRNA-disease association prediction model based on spatial consistency projection and label propagation algorithm.
    Chen M; Deng Y; Li Z; Ye Y; Zeng L; He Z; Peng G
    J Cell Mol Med; 2024 May; 28(9):e18345. PubMed ID: 38693850
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. 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]  

  • 5. 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]  

  • 6. 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]  

  • 7. A novel miRNA-disease association prediction model using dual random walk with restart and space projection federated method.
    Li A; Deng Y; Tan Y; Chen M
    PLoS One; 2021; 16(6):e0252971. PubMed ID: 34138933
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. Prediction of miRNA-disease associations based on Weighted [Formula: see text]-Nearest known neighbors and network consistency projection.
    Toprak A; Eryilmaz E
    J Bioinform Comput Biol; 2021 Feb; 19(1):2050041. PubMed ID: 33148093
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Network Consistency Projection for Human miRNA-Disease Associations Inference.
    Gu C; Liao B; Li X; Li K
    Sci Rep; 2016 Oct; 6():36054. PubMed ID: 27779232
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. 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]  

  • 13. 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]  

  • 14. Efficient framework for predicting MiRNA-disease associations based on improved hybrid collaborative filtering.
    Nie R; Li Z; You ZH; Bao W; Li J
    BMC Med Inform Decis Mak; 2021 Aug; 21(Suppl 1):254. PubMed ID: 34461870
    [TBL] [Abstract][Full Text] [Related]  

  • 15. LSGSP: a novel miRNA-disease association prediction model using a Laplacian score of the graphs and space projection federated method.
    Zhang Y; Chen M; Cheng X; Chen Z
    RSC Adv; 2019 Sep; 9(51):29747-29759. PubMed ID: 35531537
    [TBL] [Abstract][Full Text] [Related]  

  • 16. GCAEMDA: Predicting miRNA-disease associations via graph convolutional autoencoder.
    Li L; Wang YT; Ji CM; Zheng CH; Ni JC; Su YS
    PLoS Comput Biol; 2021 Dec; 17(12):e1009655. PubMed ID: 34890410
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. 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]  

  • 19. 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]  

  • 20. 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]  

    [Next]    [New Search]
    of 12.