BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

198 related articles for article (PubMed ID: 24948842)

  • 1. 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]  

  • 2. Bayesian Joint Spike-and-Slab Graphical Lasso.
    Richard Li Z; McCormick TH; Clark SJ
    Proc Mach Learn Res; 2019 Jun; 97():3877-3885. PubMed ID: 33521648
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Bayesian Covariate-Dependent Gaussian Graphical Models with Varying Structure.
    Ni Y; Stingo FC; Baladandayuthapani V
    J Mach Learn Res; 2022; 23(242):. PubMed ID: 37799290
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Bayesian Estimation for Gaussian Graphical Models: Structure Learning, Predictability, and Network Comparisons.
    Williams DR
    Multivariate Behav Res; 2021; 56(2):336-352. PubMed ID: 33739907
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. Regression-Based Bayesian Estimation and Structure Learning for Nonparanormal Graphical Models.
    Mulgrave JJ; Ghosal S
    Stat Anal Data Min; 2022 Oct; 15(5):611-629. PubMed ID: 36090618
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. The Bayesian Covariance Lasso.
    Khondker ZS; Zhu H; Chu H; Lin W; Ibrahim JG
    Stat Interface; 2013 Apr; 6(2):243-259. PubMed ID: 24551316
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. Joint Learning of Multiple Sparse Matrix Gaussian Graphical Models.
    Huang F; Chen S
    IEEE Trans Neural Netw Learn Syst; 2015 Nov; 26(11):2606-20. PubMed ID: 25751876
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. Sparse covariance estimation in heterogeneous samples.
    Rodríguez A; Lenkoski A; Dobra A
    Electron J Stat; 2011; 5():981-1014. PubMed ID: 26925189
    [TBL] [Abstract][Full Text] [Related]  

  • 13. An Expectation Conditional Maximization approach for Gaussian graphical models.
    Li ZR; McCormick TH
    J Comput Graph Stat; 2019; 28(4):767-777. PubMed ID: 33033426
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Sparse Estimation of Conditional Graphical Models With Application to Gene Networks.
    Li B; Chuns H; Zhao H
    J Am Stat Assoc; 2012 Jan; 107(497):152-167. PubMed ID: 24574574
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Compressive Sensing via Variational Bayesian Inference under Two Widely Used Priors: Modeling, Comparison and Discussion.
    Shekaramiz M; Moon TK
    Entropy (Basel); 2023 Mar; 25(3):. PubMed ID: 36981398
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Use of Wishart Prior and Simple Extensions for Sparse Precision Matrix Estimation.
    Kuismin M; Sillanpää MJ
    PLoS One; 2016; 11(2):e0148171. PubMed ID: 26828427
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Efficient Bayesian Regularization for Graphical Model Selection.
    Kundu S; Mallick BK; Baladandayuthapan V
    Bayesian Anal; 2019 Jun; 14(2):449-476. PubMed ID: 33123305
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Robust Gaussian graphical modeling via l1 penalization.
    Sun H; Li H
    Biometrics; 2012 Dec; 68(4):1197-206. PubMed ID: 23020775
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Bayesian Inference for General Gaussian Graphical Models With Application to Multivariate Lattice Data.
    Dobra A; Lenkoski A; Rodriguez A
    J Am Stat Assoc; 2011; 106(496):1418-1433. PubMed ID: 26924867
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.