BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

388 related articles for article (PubMed ID: 35879658)

  • 1. 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]  

  • 2. Predicting MiRNA-disease associations by multiple meta-paths fusion graph embedding model.
    Zhang L; Liu B; Li Z; Zhu X; Liang Z; An J
    BMC Bioinformatics; 2020 Oct; 21(1):470. PubMed ID: 33087064
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. FCGCNMDA: predicting miRNA-disease associations by applying fully connected graph convolutional networks.
    Li J; Li Z; Nie R; You Z; Bao W
    Mol Genet Genomics; 2020 Sep; 295(5):1197-1209. PubMed ID: 32500265
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. 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]  

  • 7. 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]  

  • 8. A Novel Computational Model for Predicting microRNA-Disease Associations Based on Heterogeneous Graph Convolutional Networks.
    Li C; Liu H; Hu Q; Que J; Yao J
    Cells; 2019 Aug; 8(9):. PubMed ID: 31455028
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. 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]  

  • 11. EOESGC: predicting miRNA-disease associations based on embedding of embedding and simplified graph convolutional network.
    Pang S; Zhuang Y; Wang X; Wang F; Qiao S
    BMC Med Inform Decis Mak; 2021 Nov; 21(1):319. PubMed ID: 34789236
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. 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]  

  • 14. Adaptive deep propagation graph neural network for predicting miRNA-disease associations.
    Hu H; Zhao H; Zhong T; Dong X; Wang L; Han P; Li Z
    Brief Funct Genomics; 2023 Nov; 22(5):453-462. PubMed ID: 37078739
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Predicting miRNA-disease associations based on graph random propagation network and attention network.
    Zhong T; Li Z; You ZH; Nie R; Zhao H
    Brief Bioinform; 2022 Mar; 23(2):. PubMed ID: 35079767
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. 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]  

  • 18. Combined embedding model for MiRNA-disease association prediction.
    Liu B; Zhu X; Zhang L; Liang Z; Li Z
    BMC Bioinformatics; 2021 Mar; 22(1):161. PubMed ID: 33765909
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. 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]  

    [Next]    [New Search]
    of 20.