BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

187 related articles for article (PubMed ID: 31350445)

  • 1. A Statistical Test for Differential Network Analysis Based on Inference of Gaussian Graphical Model.
    He H; Cao S; Zhang JG; Shen H; Wang YP; Deng HW
    Sci Rep; 2019 Jul; 9(1):10863. PubMed ID: 31350445
    [TBL] [Abstract][Full Text] [Related]  

  • 2. SILGGM: An extensive R package for efficient statistical inference in large-scale gene networks.
    Zhang R; Ren Z; Chen W
    PLoS Comput Biol; 2018 Aug; 14(8):e1006369. PubMed ID: 30102702
    [TBL] [Abstract][Full Text] [Related]  

  • 3. FastGGM: An Efficient Algorithm for the Inference of Gaussian Graphical Model in Biological Networks.
    Wang T; Ren Z; Ding Y; Fang Z; Sun Z; MacDonald ML; Sweet RA; Wang J; Chen W
    PLoS Comput Biol; 2016 Feb; 12(2):e1004755. PubMed ID: 26872036
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Testing Differential Gene Networks under Nonparanormal Graphical Models with False Discovery Rate Control.
    Zhang Q
    Genes (Basel); 2020 Feb; 11(2):. PubMed ID: 32033447
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A new insight into underlying disease mechanism through semi-parametric latent differential network model.
    He Y; Ji J; Xie L; Zhang X; Xue F
    BMC Bioinformatics; 2018 Dec; 19(Suppl 17):493. PubMed ID: 30591011
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Information-incorporated Gaussian graphical model for gene expression data.
    Yi H; Zhang Q; Lin C; Ma S
    Biometrics; 2022 Jun; 78(2):512-523. PubMed ID: 33527365
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Predictions of the dysregulated competing endogenous RNA signature involved in the progression of human lung adenocarcinoma.
    Yang D; He Y; Wu B; Liu R; Wang N; Wang T; Luo Y; Li Y; Liu Y
    Cancer Biomark; 2020; 29(3):399-416. PubMed ID: 32741804
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Comparative analysis of false discovery rate methods in constructing metabolic association networks.
    Koo I; Yao S; Zhang X; Kim S
    J Bioinform Comput Biol; 2014 Aug; 12(4):1450018. PubMed ID: 25152043
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Incorporating prior information into differential network analysis using non-paranormal graphical models.
    Zhang XF; Ou-Yang L; Yan H
    Bioinformatics; 2017 Aug; 33(16):2436-2445. PubMed ID: 28407042
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A Multiattribute Gaussian Graphical Model for Inferring Multiscale Regulatory Networks: An Application in Breast Cancer.
    Chiquet J; Rigaill G; Sundqvist M
    Methods Mol Biol; 2019; 1883():143-160. PubMed ID: 30547399
    [TBL] [Abstract][Full Text] [Related]  

  • 11. An Integrated Approach of Learning Genetic Networks From Genome-Wide Gene Expression Data Using Gaussian Graphical Model and Monte Carlo Method.
    Zhao H; Datta S; Duan ZH
    Bioinform Biol Insights; 2023; 17():11779322231152972. PubMed ID: 36865982
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Identification of target gene and prognostic evaluation for lung adenocarcinoma using gene expression meta-analysis, network analysis and neural network algorithms.
    Selvaraj G; Kaliamurthi S; Kaushik AC; Khan A; Wei YK; Cho WC; Gu K; Wei DQ
    J Biomed Inform; 2018 Oct; 86():120-134. PubMed ID: 30195659
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Incorporating prior biological knowledge for network-based differential gene expression analysis using differentially weighted graphical LASSO.
    Zuo Y; Cui Y; Yu G; Li R; Ressom HW
    BMC Bioinformatics; 2017 Feb; 18(1):99. PubMed ID: 28187708
    [TBL] [Abstract][Full Text] [Related]  

  • 14. MICRAT: a novel algorithm for inferring gene regulatory networks using time series gene expression data.
    Yang B; Xu Y; Maxwell A; Koh W; Gong P; Zhang C
    BMC Syst Biol; 2018 Dec; 12(Suppl 7):115. PubMed ID: 30547796
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Efficient proximal gradient algorithm for inference of differential gene networks.
    Wang C; Gao F; Giannakis GB; D'Urso G; Cai X
    BMC Bioinformatics; 2019 May; 20(1):224. PubMed ID: 31046666
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Biological network inference using low order partial correlation.
    Zuo Y; Yu G; Tadesse MG; Ressom HW
    Methods; 2014 Oct; 69(3):266-73. PubMed ID: 25003577
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Weighted lasso in graphical Gaussian modeling for large gene network estimation based on microarray data.
    Shimamura T; Imoto S; Yamaguchi R; Miyano S
    Genome Inform; 2007; 19():142-53. PubMed ID: 18546512
    [TBL] [Abstract][Full Text] [Related]  

  • 18. An integrated approach to infer dynamic protein-gene interactions - A case study of the human P53 protein.
    Wang J; Wu Q; Hu XT; Tian T
    Methods; 2016 Nov; 110():3-13. PubMed ID: 27514497
    [TBL] [Abstract][Full Text] [Related]  

  • 19. A boosting approach to structure learning of graphs with and without prior knowledge.
    Anjum S; Doucet A; Holmes CC
    Bioinformatics; 2009 Nov; 25(22):2929-36. PubMed ID: 19696047
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Node-based learning of differential networks from multi-platform gene expression data.
    Ou-Yang L; Zhang XF; Wu M; Li XL
    Methods; 2017 Oct; 129():41-49. PubMed ID: 28579401
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.