BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

151 related articles for article (PubMed ID: 38152341)

  • 1. 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]  

  • 2. 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]  

  • 3. 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]  

  • 4. 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]  

  • 5. 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]  

  • 6. 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]  

  • 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. PIntMF: Penalized Integrative Matrix Factorization method for multi-omics data.
    Pierre-Jean M; Mauger F; Deleuze JF; Le Floch E
    Bioinformatics; 2022 Jan; 38(4):900-907. PubMed ID: 34849583
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. 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]  

  • 11. 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]  

  • 12. Importance-Penalized Joint Graphical Lasso (IPJGL): differential network inference via GGMs.
    Leng J; Wu LY
    Bioinformatics; 2022 Jan; 38(3):770-777. PubMed ID: 34718410
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. 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]  

  • 15. Precision Lasso: accounting for correlations and linear dependencies in high-dimensional genomic data.
    Wang H; Lengerich BJ; Aragam B; Xing EP
    Bioinformatics; 2019 Apr; 35(7):1181-1187. PubMed ID: 30184048
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Overcoming the inadaptability of sparse group lasso for data with various group structures by stacking.
    He H; Guo X; Yu J; Ai C; Shi S
    Bioinformatics; 2022 Mar; 38(6):1542-1549. PubMed ID: 34908103
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. GRAPHICAL MODELS FOR ZERO-INFLATED SINGLE CELL GENE EXPRESSION.
    McDavid A; Gottardo R; Simon N; Drton M
    Ann Appl Stat; 2019 Jun; 13(2):848-873. PubMed ID: 31388390
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Joint Estimation of Multiple Conditional Gaussian Graphical Models.
    Huang F; Chen S; Huang SJ
    IEEE Trans Neural Netw Learn Syst; 2018 Jul; 29(7):3034-3046. PubMed ID: 28678717
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 8.