BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

217 related articles for article (PubMed ID: 31672065)

  • 1. On Penalty Parameter Selection for Estimating Network Models.
    Wysocki AC; Rhemtulla M
    Multivariate Behav Res; 2021; 56(2):288-302. PubMed ID: 31672065
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Back to the basics: Rethinking partial correlation network methodology.
    Williams DR; Rast P
    Br J Math Stat Psychol; 2020 May; 73(2):187-212. PubMed ID: 31206621
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Empirical extensions of the lasso penalty to reduce the false discovery rate in high-dimensional Cox regression models.
    Ternès N; Rotolo F; Michiels S
    Stat Med; 2016 Jul; 35(15):2561-73. PubMed ID: 26970107
    [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. 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]  

  • 6. Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models.
    Liu H; Roeder K; Wasserman L
    Adv Neural Inf Process Syst; 2010 Dec; 24(2):1432-1440. PubMed ID: 25152607
    [TBL] [Abstract][Full Text] [Related]  

  • 7. MCPeSe: Monte Carlo penalty selection for graphical lasso.
    Kuismin M; Sillanpää MJ
    Bioinformatics; 2021 May; 37(5):726-727. PubMed ID: 32805018
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Bayesian multiple Gaussian graphical models for multilevel variables from unknown classes.
    Lin J; Kim I
    Stat Methods Med Res; 2022 Apr; 31(4):594-611. PubMed ID: 35164608
    [TBL] [Abstract][Full Text] [Related]  

  • 9. A permutation approach for selecting the penalty parameter in penalized model selection.
    Sabourin JA; Valdar W; Nobel AB
    Biometrics; 2015 Dec; 71(4):1185-94. PubMed ID: 26243050
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Comparing estimation methods for psychometric networks with ordinal data.
    Johal SK; Rhemtulla M
    Psychol Methods; 2023 Dec; 28(6):1251-1272. PubMed ID: 34928677
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Learning mixed graphical models with separate sparsity parameters and stability-based model selection.
    Sedgewick AJ; Shi I; Donovan RM; Benos PV
    BMC Bioinformatics; 2016 Jun; 17 Suppl 5(Suppl 5):175. PubMed ID: 27294886
    [TBL] [Abstract][Full Text] [Related]  

  • 12. 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]  

  • 13. Order selection and sparsity in latent variable models via the ordered factor LASSO.
    Hui FKC; Tanaka E; Warton DI
    Biometrics; 2018 Dec; 74(4):1311-1319. PubMed ID: 29750847
    [TBL] [Abstract][Full Text] [Related]  

  • 14. The cluster graphical lasso for improved estimation of Gaussian graphical models.
    Tan KM; Witten D; Shojaie A
    Comput Stat Data Anal; 2015 May; 85():23-36. PubMed ID: 25642008
    [TBL] [Abstract][Full Text] [Related]  

  • 15. On Nonregularized Estimation of Psychological Networks.
    Williams DR; Rhemtulla M; Wysocki AC; Rast P
    Multivariate Behav Res; 2019; 54(5):719-750. PubMed ID: 30957629
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A Bayesian Approach for Graph-constrained Estimation for High-dimensional Regression.
    Sun H; Li H
    Int J Syst Synth Biol; 2010; 1(2):255-272. PubMed ID: 25821387
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Learning Latent Variable Gaussian Graphical Model for Biomolecular Network with Low Sample Complexity.
    Wang Y; Liu Q; Yuan B
    Comput Math Methods Med; 2016; 2016():2078214. PubMed ID: 27843485
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Simultaneous variable selection and estimation for survival data via the Gaussian seamless-
    Liu Z; Wang H
    Stat Med; 2024 Apr; 43(8):1509-1526. PubMed ID: 38320545
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation.
    Wang Y; Kang J; Kemmer PB; Guo Y
    Front Neurosci; 2016; 10():123. PubMed ID: 27242395
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 11.