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 *

138 related articles for article (PubMed ID: 31881820)

  • 1. IILLS: predicting virus-receptor interactions based on similarity and semi-supervised learning.
    Yan C; Duan G; Wu FX; Wang J
    BMC Bioinformatics; 2019 Dec; 20(Suppl 23):651. PubMed ID: 31881820
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Prediction of Virus-Receptor Interactions Based on Improving Similarities.
    Zhu L; Yan C; Duan G
    J Comput Biol; 2021 Jul; 28(7):650-659. PubMed ID: 33481654
    [TBL] [Abstract][Full Text] [Related]  

  • 3. DWNN-RLS: regularized least squares method for predicting circRNA-disease associations.
    Yan C; Wang J; Wu FX
    BMC Bioinformatics; 2018 Dec; 19(Suppl 19):520. PubMed ID: 30598076
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Predicting Drug-Drug Interactions Based on Integrated Similarity and Semi-Supervised Learning.
    Yan C; Duan G; Zhang Y; Wu FX; Pan Y; Wang J
    IEEE/ACM Trans Comput Biol Bioinform; 2022; 19(1):168-179. PubMed ID: 32310779
    [TBL] [Abstract][Full Text] [Related]  

  • 5. DDIGIP: predicting drug-drug interactions based on Gaussian interaction profile kernels.
    Yan C; Duan G; Pan Y; Wu FX; Wang J
    BMC Bioinformatics; 2019 Dec; 20(Suppl 15):538. PubMed ID: 31874609
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Prediction of virus-host infectious association by supervised learning methods.
    Zhang M; Yang L; Ren J; Ahlgren NA; Fuhrman JA; Sun F
    BMC Bioinformatics; 2017 Mar; 18(Suppl 3):60. PubMed ID: 28361670
    [TBL] [Abstract][Full Text] [Related]  

  • 7. BRWMDA:Predicting Microbe-Disease Associations Based on Similarities and Bi-Random Walk on Disease and Microbe Networks.
    Yan C; Duan G; Wu FX; Pan Y; Wang J
    IEEE/ACM Trans Comput Biol Bioinform; 2020; 17(5):1595-1604. PubMed ID: 30932846
    [TBL] [Abstract][Full Text] [Related]  

  • 8. FKL-Spa-LapRLS: an accurate method for identifying human microRNA-disease association.
    Jiang L; Xiao Y; Ding Y; Tang J; Guo F
    BMC Genomics; 2018 Dec; 19(Suppl 10):911. PubMed ID: 30598109
    [TBL] [Abstract][Full Text] [Related]  

  • 9. MCHMDA:Predicting Microbe-Disease Associations Based on Similarities and Low-Rank Matrix Completion.
    Yan C; Duan G; Wu FX; Pan Y; Wang J
    IEEE/ACM Trans Comput Biol Bioinform; 2021; 18(2):611-620. PubMed ID: 31295117
    [TBL] [Abstract][Full Text] [Related]  

  • 10. MDAKRLS: Predicting human microbe-disease association based on Kronecker regularized least squares and similarities.
    Xu D; Xu H; Zhang Y; Wang M; Chen W; Gao R
    J Transl Med; 2021 Feb; 19(1):66. PubMed ID: 33579301
    [TBL] [Abstract][Full Text] [Related]  

  • 11. LRLSHMDA: Laplacian Regularized Least Squares for Human Microbe-Disease Association prediction.
    Wang F; Huang ZA; Chen X; Zhu Z; Wen Z; Zhao J; Yan GY
    Sci Rep; 2017 Aug; 7(1):7601. PubMed ID: 28790448
    [TBL] [Abstract][Full Text] [Related]  

  • 12. MDA-SKF: Similarity Kernel Fusion for Accurately Discovering miRNA-Disease Association.
    Jiang L; Ding Y; Tang J; Guo F
    Front Genet; 2018; 9():618. PubMed ID: 30619454
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Drug Repositioning by Integrating Known Disease-Gene and Drug-Target Associations in a Semi-supervised Learning Model.
    Le DH; Nguyen-Ngoc D
    Acta Biotheor; 2018 Dec; 66(4):315-331. PubMed ID: 29700660
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Prognostic outcome prediction by semi-supervised least squares classification.
    Shi M; Sheng Z; Tang H
    Brief Bioinform; 2021 Jul; 22(4):. PubMed ID: 33094318
    [TBL] [Abstract][Full Text] [Related]  

  • 15. SNMFSMMA: using symmetric nonnegative matrix factorization and Kronecker regularized least squares to predict potential small molecule-microRNA association.
    Zhao Y; Chen X; Yin J; Qu J
    RNA Biol; 2020 Feb; 17(2):281-291. PubMed ID: 31739716
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A Semi-Supervised Learning Algorithm for Predicting Four Types MiRNA-Disease Associations by Mutual Information in a Heterogeneous Network.
    Zhang X; Yin J; Zhang X
    Genes (Basel); 2018 Mar; 9(3):. PubMed ID: 29498680
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A Drug-Target Network-Based Supervised Machine Learning Repurposing Method Allowing the Use of Multiple Heterogeneous Information Sources.
    Nascimento ACA; Prudêncio RBC; Costa IG
    Methods Mol Biol; 2019; 1903():281-289. PubMed ID: 30547449
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Predicting the hosts of prokaryotic viruses using GCN-based semi-supervised learning.
    Shang J; Sun Y
    BMC Biol; 2021 Nov; 19(1):250. PubMed ID: 34819064
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Prediction of disease-related metabolites using bi-random walks.
    Lei X; Tie J
    PLoS One; 2019; 14(11):e0225380. PubMed ID: 31730648
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.