BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

158 related articles for article (PubMed ID: 34654363)

  • 1. Tailored graphical lasso for data integration in gene network reconstruction.
    Lingjærde C; Lien TG; Borgan Ø; Bergholtz H; Glad IK
    BMC Bioinformatics; 2021 Oct; 22(1):498. PubMed ID: 34654363
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Gene Network Reconstruction by Integration of Prior Biological Knowledge.
    Li Y; Jackson SA
    G3 (Bethesda); 2015 Mar; 5(6):1075-9. PubMed ID: 25823587
    [TBL] [Abstract][Full Text] [Related]  

  • 4. An Augmented High-Dimensional Graphical Lasso Method to Incorporate Prior Biological Knowledge for Global Network Learning.
    Zhuang Y; Xing F; Ghosh D; Banaei-Kashani F; Bowler RP; Kechris K
    Front Genet; 2021; 12():760299. PubMed ID: 35154240
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Weighted Fused Pathway Graphical Lasso for Joint Estimation of Multiple Gene Networks.
    Wu N; Huang J; Zhang XF; Ou-Yang L; He S; Zhu Z; Xie W
    Front Genet; 2019; 10():623. PubMed ID: 31396259
    [TBL] [Abstract][Full Text] [Related]  

  • 6. StabJGL: a stability approach to sparsity and similarity selection in multiple-network reconstruction.
    Lingjærde C; Richardson S
    Bioinform Adv; 2023; 3(1):vbad185. PubMed ID: 38152341
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Regularized estimation of large-scale gene association networks using graphical Gaussian models.
    Krämer N; Schäfer J; Boulesteix AL
    BMC Bioinformatics; 2009 Nov; 10():384. PubMed ID: 19930695
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. ℓ 1-Penalized censored Gaussian graphical model.
    Augugliaro L; Abbruzzo A; Vinciotti V
    Biostatistics; 2020 Apr; 21(2):e1-e16. PubMed ID: 30203001
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Inference of radio-responsive gene regulatory networks using the graphical lasso algorithm.
    Oh JH; Deasy JO
    BMC Bioinformatics; 2014; 15 Suppl 7(Suppl 7):S5. PubMed ID: 25077716
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Exact Covariance Thresholding into Connected Components for Large-Scale Graphical Lasso.
    Mazumder R; Hastie T
    J Mach Learn Res; 2012 Mar; 13():781-794. PubMed ID: 25392704
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Learning directed acyclic graphical structures with genetical genomics data.
    Gao B; Cui Y
    Bioinformatics; 2015 Dec; 31(24):3953-60. PubMed ID: 26338766
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Inferring metabolic networks using the Bayesian adaptive graphical lasso with informative priors.
    Peterson C; Vannucci M; Karakas C; Choi W; Ma L; Maletić-Savatić M
    Stat Interface; 2013 Oct; 6(4):547-558. PubMed ID: 24533172
    [TBL] [Abstract][Full Text] [Related]  

  • 15. The joint graphical lasso for inverse covariance estimation across multiple classes.
    Danaher P; Wang P; Witten DM
    J R Stat Soc Series B Stat Methodol; 2014 Mar; 76(2):373-397. PubMed ID: 24817823
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. Bayesian sparse graphical models and their mixtures.
    Talluri R; Baladandayuthapani V; Mallick BK
    Stat; 2014 Jan; 3(1):109-125. PubMed ID: 24948842
    [TBL] [Abstract][Full Text] [Related]  

  • 18. RCFGL: Rapid Condition adaptive Fused Graphical Lasso and application to modeling brain region co-expression networks.
    Seal S; Li Q; Basner EB; Saba LM; Kechris K
    PLoS Comput Biol; 2023 Jan; 19(1):e1010758. PubMed ID: 36607897
    [TBL] [Abstract][Full Text] [Related]  

  • 19. The graphical lasso: New insights and alternatives.
    Mazumder R; Hastie T
    Electron J Stat; 2012 Nov; 6():2125-2149. PubMed ID: 25558297
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A scale-free structure prior for graphical models with applications in functional genomics.
    Sheridan P; Kamimura T; Shimodaira H
    PLoS One; 2010 Nov; 5(11):e13580. PubMed ID: 21079769
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.