BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

568 related articles for article (PubMed ID: 31229287)

  • 1. A mating advice system in dairy cattle incorporating genomic information.
    Carthy TR; McCarthy J; Berry DP
    J Dairy Sci; 2019 Sep; 102(9):8210-8220. PubMed ID: 31229287
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Imputation of non-genotyped F1 dams to improve genetic gain in swine crossbreeding programs.
    See GM; Fix JS; Schwab CR; Spangler ML
    J Anim Sci; 2022 May; 100(5):. PubMed ID: 35451025
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Novel strategies to minimize progeny inbreeding while maximizing genetic gain using genomic information.
    Pryce JE; Hayes BJ; Goddard ME
    J Dairy Sci; 2012 Jan; 95(1):377-88. PubMed ID: 22192217
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Controlling inbreeding and maximizing genetic gain using semi-definite programming with pedigree-based and genomic relationships.
    Schierenbeck S; Pimentel EC; Tietze M; Körte J; Reents R; Reinhardt F; Simianer H; König S
    J Dairy Sci; 2011 Dec; 94(12):6143-52. PubMed ID: 22118102
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Confirmation and discovery of maternal grandsires and great-grandsires in dairy cattle.
    VanRaden PM; Cooper TA; Wiggans GR; O'Connell JR; Bacheller LR
    J Dairy Sci; 2013 Mar; 96(3):1874-9. PubMed ID: 23332849
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Improved dairy cattle mating plans at herd level using genomic information.
    Bérodier M; Berg P; Meuwissen T; Boichard D; Brochard M; Ducrocq V
    Animal; 2021 Jan; 15(1):100016. PubMed ID: 33516018
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Imputation of non-genotyped sheep from the genotypes of their mates and resulting progeny.
    Berry DP; McHugh N; Randles S; Wall E; McDermott K; Sargolzaei M; O'Brien AC
    Animal; 2018 Feb; 12(2):191-198. PubMed ID: 28712375
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Heritabilities and genetic correlations in the same traits across different strata of herds created according to continuous genomic, genetic, and phenotypic descriptors.
    Yin T; König S
    J Dairy Sci; 2018 Mar; 101(3):2171-2186. PubMed ID: 29248231
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Development of genomic predictions for Angus cattle in Brazil incorporating genotypes from related American sires.
    Campos GS; Cardoso FF; Gomes CCG; Domingues R; de Almeida Regitano LC; de Sena Oliveira MC; de Oliveira HN; Carvalheiro R; Albuquerque LG; Miller S; Misztal I; Lourenco D
    J Anim Sci; 2022 Feb; 100(2):. PubMed ID: 35031806
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Mating programs including genomic relationships and dominance effects.
    Sun C; VanRaden PM; O'Connell JR; Weigel KA; Gianola D
    J Dairy Sci; 2013; 96(12):8014-23. PubMed ID: 24119810
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Imputation of ungenotyped parental genotypes in dairy and beef cattle from progeny genotypes.
    Berry DP; McParland S; Kearney JF; Sargolzaei M; Mullen MP
    Animal; 2014 Jun; 8(6):895-903. PubMed ID: 24840560
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Estimation of genetic parameters and breeding values for feed intake and energy balance using pedigree relationships or single-step genomic evaluation in Holstein Friesian cows.
    Harder I; Stamer E; Junge W; Thaller G
    J Dairy Sci; 2020 Mar; 103(3):2498-2513. PubMed ID: 31864743
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Genomic imputation and evaluation using high-density Holstein genotypes.
    VanRaden PM; Null DJ; Sargolzaei M; Wiggans GR; Tooker ME; Cole JB; Sonstegard TS; Connor EE; Winters M; van Kaam JB; Valentini A; Van Doormaal BJ; Faust MA; Doak GA
    J Dairy Sci; 2013 Jan; 96(1):668-78. PubMed ID: 23063157
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Genomic selection for tolerance to heat stress in Australian dairy cattle.
    Nguyen TTT; Bowman PJ; Haile-Mariam M; Pryce JE; Hayes BJ
    J Dairy Sci; 2016 Apr; 99(4):2849-2862. PubMed ID: 27037467
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Imputation of genotypes from low density (50,000 markers) to high density (700,000 markers) of cows from research herds in Europe, North America, and Australasia using 2 reference populations.
    Pryce JE; Johnston J; Hayes BJ; Sahana G; Weigel KA; McParland S; Spurlock D; Krattenmacher N; Spelman RJ; Wall E; Calus MP
    J Dairy Sci; 2014 Mar; 97(3):1799-811. PubMed ID: 24472132
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Short communication: Single-step genomic evaluation of milk production traits using multiple-trait random regression model in Chinese Holsteins.
    Kang H; Ning C; Zhou L; Zhang S; Yan Q; Liu JF
    J Dairy Sci; 2018 Dec; 101(12):11143-11149. PubMed ID: 30268613
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Leveraging low-density crossbred genotypes to offset crossbred phenotypes and their impact on purebred predictions.
    Leite NG; Chen CY; Herring WO; Holl J; Tsuruta S; Lourenco D
    J Anim Sci; 2022 Dec; 100(12):. PubMed ID: 36309902
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Genomic predictions based on animal models using genotype imputation on a national scale in Norwegian Red cattle.
    Meuwissen TH; Svendsen M; Solberg T; Ødegård J
    Genet Sel Evol; 2015 Oct; 47():79. PubMed ID: 26464226
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Genotyping more cows increases genetic gain and reduces rate of true inbreeding in a dairy cattle breeding scheme using female reproductive technologies.
    Thomasen JR; Liu H; Sørensen AC
    J Dairy Sci; 2020 Jan; 103(1):597-606. PubMed ID: 31733861
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Use of a Bayesian model including QTL markers increases prediction reliability when test animals are distant from the reference population.
    Ma P; Lund MS; Aamand GP; Su G
    J Dairy Sci; 2019 Aug; 102(8):7237-7247. PubMed ID: 31155255
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 29.