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Journal Abstract Search

136 related items for PubMed ID: 25053450

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  • 3. Genomic selection in sugar beet breeding populations.
    Würschum T, Reif JC, Kraft T, Janssen G, Zhao Y.
    BMC Genet; 2013 Sep 18; 14():85. PubMed ID: 24047500
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  • 4. Genetic basis of agronomically important traits in sugar beet (Beta vulgaris L.) investigated with joint linkage association mapping.
    Reif JC, Liu W, Gowda M, Maurer HP, Möhring J, Fischer S, Schechert A, Würschum T.
    Theor Appl Genet; 2010 Nov 18; 121(8):1489-99. PubMed ID: 20640844
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  • 5. Accuracy of prediction of simulated polygenic phenotypes and their underlying quantitative trait loci genotypes using real or imputed whole-genome markers in cattle.
    Hassani S, Saatchi M, Fernando RL, Garrick DJ.
    Genet Sel Evol; 2015 Dec 23; 47():99. PubMed ID: 26698091
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  • 6. Genome-wide association mapping of agronomic traits in sugar beet.
    Würschum T, Maurer HP, Kraft T, Janssen G, Nilsson C, Reif JC.
    Theor Appl Genet; 2011 Nov 23; 123(7):1121-31. PubMed ID: 21761161
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  • 7. Reduction in accuracy of genomic prediction for ordered categorical data compared to continuous observations.
    Kizilkaya K, Fernando RL, Garrick DJ.
    Genet Sel Evol; 2014 Jun 09; 46(1):37. PubMed ID: 24912924
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  • 8. Genomic prediction ability for beef fatty acid profile in Nelore cattle using different pseudo-phenotypes.
    Chiaia HLJ, Peripolli E, de Oliveira Silva RM, Feitosa FLB, de Lemos MVA, Berton MP, Olivieri BF, Espigolan R, Tonussi RL, Gordo DGM, de Albuquerque LG, de Oliveira HN, Ferrinho AM, Mueller LF, Kluska S, Tonhati H, Pereira ASC, Aguilar I, Baldi F.
    J Appl Genet; 2018 Nov 09; 59(4):493-501. PubMed ID: 30251238
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  • 10. Effects of number of training generations on genomic prediction for various traits in a layer chicken population.
    Weng Z, Wolc A, Shen X, Fernando RL, Dekkers JC, Arango J, Settar P, Fulton JE, O'Sullivan NP, Garrick DJ.
    Genet Sel Evol; 2016 Mar 19; 48():22. PubMed ID: 26992471
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  • 11. Improving accuracy of genomic predictions within and between dairy cattle breeds with imputed high-density single nucleotide polymorphism panels.
    Erbe M, Hayes BJ, Matukumalli LK, Goswami S, Bowman PJ, Reich CM, Mason BA, Goddard ME.
    J Dairy Sci; 2012 Jul 19; 95(7):4114-29. PubMed ID: 22720968
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  • 12. Development of genomic predictions for harvest and carcass weight in channel catfish.
    Garcia ALS, Bosworth B, Waldbieser G, Misztal I, Tsuruta S, Lourenco DAL.
    Genet Sel Evol; 2018 Dec 14; 50(1):66. PubMed ID: 30547740
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  • 13. Genomic predictions can accelerate selection for resistance against Piscirickettsia salmonis in Atlantic salmon (Salmo salar).
    Bangera R, Correa K, Lhorente JP, Figueroa R, Yáñez JM.
    BMC Genomics; 2017 Jan 31; 18(1):121. PubMed ID: 28143402
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  • 17. Comparison of conventional BLUP and single-step genomic BLUP evaluations for yearling weight and carcass traits in Hanwoo beef cattle using single trait and multi-trait models.
    Mehrban H, Lee DH, Naserkheil M, Moradi MH, Ibáñez-Escriche N.
    PLoS One; 2019 Jan 31; 14(10):e0223352. PubMed ID: 31609979
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  • 20. The genome of the recently domesticated crop plant sugar beet (Beta vulgaris).
    Dohm JC, Minoche AE, Holtgräwe D, Capella-Gutiérrez S, Zakrzewski F, Tafer H, Rupp O, Sörensen TR, Stracke R, Reinhardt R, Goesmann A, Kraft T, Schulz B, Stadler PF, Schmidt T, Gabaldón T, Lehrach H, Weisshaar B, Himmelbauer H.
    Nature; 2014 Jan 23; 505(7484):546-9. PubMed ID: 24352233
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