BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

138 related articles for article (PubMed ID: 35709188)

  • 1. Selecting predictive biomarkers from genomic data.
    Frommlet F; Szulc P; König F; Bogdan M
    PLoS One; 2022; 17(6):e0269369. PubMed ID: 35709188
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Bayesian two-step Lasso strategy for biomarker selection in personalized medicine development for time-to-event endpoints.
    Gu X; Yin G; Lee JJ
    Contemp Clin Trials; 2013 Nov; 36(2):642-50. PubMed ID: 24075829
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Analyzing genome-wide association studies with an FDR controlling modification of the Bayesian Information Criterion.
    Dolejsi E; Bodenstorfer B; Frommlet F
    PLoS One; 2014; 9(7):e103322. PubMed ID: 25061809
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Application of statistical machine learning in biomarker selection.
    Vashistha R; Noor Z; Dasgupta S; Pu J; Deng S
    Sci Rep; 2023 Oct; 13(1):18331. PubMed ID: 37884606
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.).
    Resende MF; Muñoz P; Resende MD; Garrick DJ; Fernando RL; Davis JM; Jokela EJ; Martin TA; Peter GF; Kirst M
    Genetics; 2012 Apr; 190(4):1503-10. PubMed ID: 22271763
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Integrating genomic signatures for treatment selection with Bayesian predictive failure time models.
    Ma J; Hobbs BP; Stingo FC
    Stat Methods Med Res; 2018 Jul; 27(7):2093-2113. PubMed ID: 27807177
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Efficiency of genomic selection using Bayesian multi-marker models for traits selected to reflect a wide range of heritabilities and frequencies of detected quantitative traits loci in mice.
    Kapell DN; Sorensen D; Su G; Janss LL; Ashworth CJ; Roehe R
    BMC Genet; 2012 May; 13():42. PubMed ID: 22651804
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Accuracy of genomic predictions in Bos indicus (Nellore) cattle.
    Neves HH; Carvalheiro R; O'Brien AM; Utsunomiya YT; do Carmo AS; Schenkel FS; Sölkner J; McEwan JC; Van Tassell CP; Cole JB; da Silva MV; Queiroz SA; Sonstegard TS; Garcia JF
    Genet Sel Evol; 2014 Feb; 46(1):17. PubMed ID: 24575732
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Genome-wide prediction using Bayesian additive regression trees.
    Waldmann P
    Genet Sel Evol; 2016 Jun; 48(1):42. PubMed ID: 27286957
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Application of Bayesian least absolute shrinkage and selection operator (LASSO) and BayesCπ methods for genomic selection in French Holstein and Montbéliarde breeds.
    Colombani C; Legarra A; Fritz S; Guillaume F; Croiseau P; Ducrocq V; Robert-Granié C
    J Dairy Sci; 2013 Jan; 96(1):575-91. PubMed ID: 23127905
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Overview of LASSO-related penalized regression methods for quantitative trait mapping and genomic selection.
    Li Z; Sillanpää MJ
    Theor Appl Genet; 2012 Aug; 125(3):419-35. PubMed ID: 22622521
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Genomic best linear unbiased prediction method reflecting the degree of linkage disequilibrium.
    Nishio M; Satoh M
    J Anim Breed Genet; 2015 Oct; 132(5):357-65. PubMed ID: 25866073
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Improving genomic prediction accuracy for meat tenderness in Nellore cattle using artificial neural networks.
    Brito Lopes F; Magnabosco CU; Passafaro TL; Brunes LC; Costa MFO; Eifert EC; Narciso MG; Rosa GJM; Lobo RB; Baldi F
    J Anim Breed Genet; 2020 Sep; 137(5):438-448. PubMed ID: 32020678
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Bayesian predictive modeling for genomic based personalized treatment selection.
    Ma J; Stingo FC; Hobbs BP
    Biometrics; 2016 Jun; 72(2):575-83. PubMed ID: 26575856
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Robust estimation of the expected survival probabilities from high-dimensional Cox models with biomarker-by-treatment interactions in randomized clinical trials.
    Ternès N; Rotolo F; Michiels S
    BMC Med Res Methodol; 2017 May; 17(1):83. PubMed ID: 28532387
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A Bayesian outlier criterion to detect SNPs under selection in large data sets.
    Gautier M; Hocking TD; Foulley JL
    PLoS One; 2010 Aug; 5(8):e11913. PubMed ID: 20689851
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Predictive genomics of cardioembolic stroke.
    Ramoni RB; Himes BE; Sale MM; Furie KL; Ramoni MF
    Stroke; 2009 Mar; 40(3 Suppl):S67-70. PubMed ID: 19064790
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Prediction of non-muscle invasive bladder cancer outcomes assessed by innovative multimarker prognostic models.
    López de Maturana E; Picornell A; Masson-Lecomte A; Kogevinas M; Márquez M; Carrato A; Tardón A; Lloreta J; García-Closas M; Silverman D; Rothman N; Chanock S; Real FX; Goddard ME; Malats N;
    BMC Cancer; 2016 Jun; 16():351. PubMed ID: 27259534
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Comparison of Bayesian models to estimate direct genomic values in multi-breed commercial beef cattle.
    Rolf MM; Garrick DJ; Fountain T; Ramey HR; Weaber RL; Decker JE; Pollak EJ; Schnabel RD; Taylor JF
    Genet Sel Evol; 2015 Apr; 47(1):23. PubMed ID: 25884158
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.