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 *

231 related articles for article (PubMed ID: 29970398)

  • 1. Optimising Genomic Selection in Wheat: Effect of Marker Density, Population Size and Population Structure on Prediction Accuracy.
    Norman A; Taylor J; Edwards J; Kuchel H
    G3 (Bethesda); 2018 Aug; 8(9):2889-2899. PubMed ID: 29970398
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Potential and limits to unravel the genetic architecture and predict the variation of Fusarium head blight resistance in European winter wheat (Triticum aestivum L.).
    Jiang Y; Zhao Y; Rodemann B; Plieske J; Kollers S; Korzun V; Ebmeyer E; Argillier O; Hinze M; Ling J; Röder MS; Ganal MW; Mette MF; Reif JC
    Heredity (Edinb); 2015 Mar; 114(3):318-26. PubMed ID: 25388142
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Accuracy of genomic selection for grain yield and agronomic traits in soft red winter wheat.
    Lozada DN; Mason RE; Sarinelli JM; Brown-Guedira G
    BMC Genet; 2019 Nov; 20(1):82. PubMed ID: 31675927
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Canopy Temperature and Vegetation Indices from High-Throughput Phenotyping Improve Accuracy of Pedigree and Genomic Selection for Grain Yield in Wheat.
    Rutkoski J; Poland J; Mondal S; Autrique E; Pérez LG; Crossa J; Reynolds M; Singh R
    G3 (Bethesda); 2016 Sep; 6(9):2799-808. PubMed ID: 27402362
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Improving Prediction Accuracy Using Multi-allelic Haplotype Prediction and Training Population Optimization in Wheat.
    Sallam AH; Conley E; Prakapenka D; Da Y; Anderson JA
    G3 (Bethesda); 2020 Jul; 10(7):2265-2273. PubMed ID: 32371453
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A classic approach for determining genomic prediction accuracy under terminal drought stress and well-watered conditions in wheat landraces and cultivars.
    Shabannejad M; Bihamta MR; Majidi-Hervan E; Alipour H; Ebrahimi A
    PLoS One; 2021; 16(3):e0247824. PubMed ID: 33667255
    [TBL] [Abstract][Full Text] [Related]  

  • 7. The effects of training population design on genomic prediction accuracy in wheat.
    Edwards SM; Buntjer JB; Jackson R; Bentley AR; Lage J; Byrne E; Burt C; Jack P; Berry S; Flatman E; Poupard B; Smith S; Hayes C; Gaynor RC; Gorjanc G; Howell P; Ober E; Mackay IJ; Hickey JM
    Theor Appl Genet; 2019 Jul; 132(7):1943-1952. PubMed ID: 30888431
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Training population selection and use of fixed effects to optimize genomic predictions in a historical USA winter wheat panel.
    Sarinelli JM; Murphy JP; Tyagi P; Holland JB; Johnson JW; Mergoum M; Mason RE; Babar A; Harrison S; Sutton R; Griffey CA; Brown-Guedira G
    Theor Appl Genet; 2019 Apr; 132(4):1247-1261. PubMed ID: 30680419
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Genomic selection across multiple breeding cycles in applied bread wheat breeding.
    Michel S; Ametz C; Gungor H; Epure D; Grausgruber H; Löschenberger F; Buerstmayr H
    Theor Appl Genet; 2016 Jun; 129(6):1179-89. PubMed ID: 27067826
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Increased prediction accuracy in wheat breeding trials using a marker × environment interaction genomic selection model.
    Lopez-Cruz M; Crossa J; Bonnett D; Dreisigacker S; Poland J; Jannink JL; Singh RP; Autrique E; de los Campos G
    G3 (Bethesda); 2015 Feb; 5(4):569-82. PubMed ID: 25660166
    [TBL] [Abstract][Full Text] [Related]  

  • 11. BWGS: A R package for genomic selection and its application to a wheat breeding programme.
    Charmet G; Tran LG; Auzanneau J; Rincent R; Bouchet S
    PLoS One; 2020; 15(4):e0222733. PubMed ID: 32240182
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Hyperspectral Reflectance-Derived Relationship Matrices for Genomic Prediction of Grain Yield in Wheat.
    Krause MR; González-Pérez L; Crossa J; Pérez-Rodríguez P; Montesinos-López O; Singh RP; Dreisigacker S; Poland J; Rutkoski J; Sorrells M; Gore MA; Mondal S
    G3 (Bethesda); 2019 Apr; 9(4):1231-1247. PubMed ID: 30796086
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat.
    Liu G; Zhao Y; Gowda M; Longin CF; Reif JC; Mette MF
    PLoS One; 2016; 11(7):e0158635. PubMed ID: 27383841
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Optimizing Training Population Data and Validation of Genomic Selection for Economic Traits in Soft Winter Wheat.
    Hoffstetter A; Cabrera A; Huang M; Sneller C
    G3 (Bethesda); 2016 Sep; 6(9):2919-28. PubMed ID: 27440921
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Optimizing Low-Cost Genotyping and Imputation Strategies for Genomic Selection in Atlantic Salmon.
    Tsairidou S; Hamilton A; Robledo D; Bron JE; Houston RD
    G3 (Bethesda); 2020 Feb; 10(2):581-590. PubMed ID: 31826882
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A comparison between genotyping-by-sequencing and array-based scoring of SNPs for genomic prediction accuracy in winter wheat.
    Elbasyoni IS; Lorenz AJ; Guttieri M; Frels K; Baenziger PS; Poland J; Akhunov E
    Plant Sci; 2018 May; 270():123-130. PubMed ID: 29576064
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Effects of marker density and population structure on the genomic prediction accuracy for growth trait in Pacific white shrimp Litopenaeus vannamei.
    Wang Q; Yu Y; Yuan J; Zhang X; Huang H; Li F; Xiang J
    BMC Genet; 2017 May; 18(1):45. PubMed ID: 28514941
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Genomic prediction in French Charolais beef cattle using high-density single nucleotide polymorphism markers.
    Gunia M; Saintilan R; Venot E; Hozé C; Fouilloux MN; Phocas F
    J Anim Sci; 2014 Aug; 92(8):3258-69. PubMed ID: 24948648
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Multi-generational imputation of single nucleotide polymorphism marker genotypes and accuracy of genomic selection.
    Toghiani S; Aggrey SE; Rekaya R
    Animal; 2016 Jul; 10(7):1077-85. PubMed ID: 27076192
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Accounting for Genotype-by-Environment Interactions and Residual Genetic Variation in Genomic Selection for Water-Soluble Carbohydrate Concentration in Wheat.
    Ovenden B; Milgate A; Wade LJ; Rebetzke GJ; Holland JB
    G3 (Bethesda); 2018 May; 8(6):1909-1919. PubMed ID: 29661842
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.