These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

266 related articles for article (PubMed ID: 24727289)

  • 1. Parametric and nonparametric statistical methods for genomic selection of traits with additive and epistatic genetic architectures.
    Howard R; Carriquiry AL; Beavis WD
    G3 (Bethesda); 2014 Apr; 4(6):1027-46. PubMed ID: 24727289
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Predictive ability of genome-assisted statistical models under various forms of gene action.
    Momen M; Mehrgardi AA; Sheikhi A; Kranis A; Tusell L; Morota G; Rosa GJM; Gianola D
    Sci Rep; 2018 Aug; 8(1):12309. PubMed ID: 30120288
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Effect of genetic architecture on the prediction accuracy of quantitative traits in samples of unrelated individuals.
    Morgante F; Huang W; Maltecca C; Mackay TFC
    Heredity (Edinb); 2018 Jun; 120(6):500-514. PubMed ID: 29426878
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Comparison of parametric, semiparametric and nonparametric methods in genomic evaluation.
    Sahebalam H; Gholizadeh M; Hafezian H; Farhadi A
    J Genet; 2019 Nov; 98():. PubMed ID: 31767821
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Modeling Epistasis in Genomic Selection.
    Jiang Y; Reif JC
    Genetics; 2015 Oct; 201(2):759-68. PubMed ID: 26219298
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Application of Response Surface Methods To Determine Conditions for Optimal Genomic Prediction.
    Howard R; Carriquiry AL; Beavis WD
    G3 (Bethesda); 2017 Sep; 7(9):3103-3113. PubMed ID: 28720710
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Genome-wide prediction of maize single-cross performance, considering non-additive genetic effects.
    Santos JP; Pereira HD; Von Pinho RG; Pires LP; Camargos RB; Balestre M
    Genet Mol Res; 2015 Dec; 14(4):18471-84. PubMed ID: 26782495
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Ridge, Lasso and Bayesian additive-dominance genomic models.
    Azevedo CF; de Resende MD; E Silva FF; Viana JM; Valente MS; Resende MF; Muñoz P
    BMC Genet; 2015 Aug; 16():105. PubMed ID: 26303864
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Multi-trait Improvement by Predicting Genetic Correlations in Breeding Crosses.
    Neyhart JL; Lorenz AJ; Smith KP
    G3 (Bethesda); 2019 Oct; 9(10):3153-3165. PubMed ID: 31358561
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A Unified and Comprehensible View of Parametric and Kernel Methods for Genomic Prediction with Application to Rice.
    Jacquin L; Cao TV; Ahmadi N
    Front Genet; 2016; 7():145. PubMed ID: 27555865
    [TBL] [Abstract][Full Text] [Related]  

  • 12. An empirical Bayes method for estimating epistatic effects of quantitative trait loci.
    Xu S
    Biometrics; 2007 Jun; 63(2):513-21. PubMed ID: 17688503
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Genome-enabled prediction of genetic values using radial basis function neural networks.
    González-Camacho JM; de Los Campos G; Pérez P; Gianola D; Cairns JE; Mahuku G; Babu R; Crossa J
    Theor Appl Genet; 2012 Aug; 125(4):759-71. PubMed ID: 22566067
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep learning versus parametric and ensemble methods for genomic prediction of complex phenotypes.
    Abdollahi-Arpanahi R; Gianola D; Peñagaricano F
    Genet Sel Evol; 2020 Feb; 52(1):12. PubMed ID: 32093611
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Genome-wide prediction of traits with different genetic architecture through efficient variable selection.
    Wimmer V; Lehermeier C; Albrecht T; Auinger HJ; Wang Y; Schön CC
    Genetics; 2013 Oct; 195(2):573-87. PubMed ID: 23934883
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Prediction of genetic values of quantitative traits with epistatic effects in plant breeding populations.
    Wang D; Salah El-Basyoni I; Stephen Baenziger P; Crossa J; Eskridge KM; Dweikat I
    Heredity (Edinb); 2012 Nov; 109(5):313-9. PubMed ID: 22892636
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Beyond Genomic Prediction: Combining Different Types of
    Schrag TA; Westhues M; Schipprack W; Seifert F; Thiemann A; Scholten S; Melchinger AE
    Genetics; 2018 Apr; 208(4):1373-1385. PubMed ID: 29363551
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Genome-Enabled Estimates of Additive and Nonadditive Genetic Variances and Prediction of Apple Phenotypes Across Environments.
    Kumar S; Molloy C; Muñoz P; Daetwyler H; Chagné D; Volz R
    G3 (Bethesda); 2015 Oct; 5(12):2711-8. PubMed ID: 26497141
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Bayesian neural networks with variable selection for prediction of genotypic values.
    van Bergen GHH; Duenk P; Albers CA; Bijma P; Calus MPL; Wientjes YCJ; Kappen HJ
    Genet Sel Evol; 2020 May; 52(1):26. PubMed ID: 32414320
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Phantom Epistasis in Genomic Selection: On the Predictive Ability of Epistatic Models.
    Schrauf MF; Martini JWR; Simianer H; de Los Campos G; Cantet R; Freudenthal J; Korte A; Munilla S
    G3 (Bethesda); 2020 Sep; 10(9):3137-3145. PubMed ID: 32709618
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.