BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

237 related articles for article (PubMed ID: 31154259)

  • 1. MAMDA: Inferring microRNA-Disease associations with manifold alignment.
    Yan F; Zheng Y; Jia W; Hou S; Xiao R
    Comput Biol Med; 2019 Jul; 110():156-163. PubMed ID: 31154259
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. 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]  

  • 4. DNRLMF-MDA:Predicting microRNA-Disease Associations Based on Similarities of microRNAs and Diseases.
    Yan C; Wang J; Ni P; Lan W; Wu FX; Pan Y
    IEEE/ACM Trans Comput Biol Bioinform; 2019; 16(1):233-243. PubMed ID: 29990253
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. 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]  

  • 7. 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]  

  • 8. Inferring the Disease-Associated miRNAs Based on Network Representation Learning and Convolutional Neural Networks.
    Xuan P; Sun H; Wang X; Zhang T; Pan S
    Int J Mol Sci; 2019 Jul; 20(15):. PubMed ID: 31349729
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. Integrating random walk and binary regression to identify novel miRNA-disease association.
    Niu YW; Wang GH; Yan GY; Chen X
    BMC Bioinformatics; 2019 Jan; 20(1):59. PubMed ID: 30691413
    [TBL] [Abstract][Full Text] [Related]  

  • 11. MicroRNA-disease association prediction by matrix tri-factorization.
    Li H; Guo Y; Cai M; Li L
    BMC Genomics; 2020 Nov; 21(Suppl 10):617. PubMed ID: 33208088
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 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. Human disease MiRNA inference by combining target information based on heterogeneous manifolds.
    Ding P; Luo J; Liang C; Xiao Q; Cao B
    J Biomed Inform; 2018 Apr; 80():26-36. PubMed ID: 29481877
    [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. MicroRNAs and complex diseases: from experimental results to computational models.
    Chen X; Xie D; Zhao Q; You ZH
    Brief Bioinform; 2019 Mar; 20(2):515-539. PubMed ID: 29045685
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Integration of Multiple Genomic and Phenotype Data to Infer Novel miRNA-Disease Associations.
    Shi H; Zhang G; Zhou M; Cheng L; Yang H; Wang J; Sun J; Wang Z
    PLoS One; 2016; 11(2):e0148521. PubMed ID: 26849207
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Predicting MicroRNA-Disease Associations Based on Improved MicroRNA and Disease Similarities.
    Lan W; Wang J; Li M; Liu J; Wu FX; Pan Y
    IEEE/ACM Trans Comput Biol Bioinform; 2018; 15(6):1774-1782. PubMed ID: 27392365
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.