BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

325 related articles for article (PubMed ID: 29624705)

  • 21. Genomic predictions based on a joint reference population for the Nordic Red cattle breeds.
    Zhou L; Heringstad B; Su G; Guldbrandtsen B; Meuwissen TH; Svendsen M; Grove H; Nielsen US; Lund MS
    J Dairy Sci; 2014 Jul; 97(7):4485-96. PubMed ID: 24792791
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Genetic evaluations and genome-wide association studies for specific digital dermatitis diagnoses in dairy cows considering genotype × housing system interactions.
    Sölzer N; Brügemann K; Yin T; König S
    J Dairy Sci; 2024 Jun; 107(6):3724-3737. PubMed ID: 38216046
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Genomic prediction using imputed whole-genome sequence data in Holstein Friesian cattle.
    van Binsbergen R; Calus MP; Bink MC; van Eeuwijk FA; Schrooten C; Veerkamp RF
    Genet Sel Evol; 2015 Sep; 47(1):71. PubMed ID: 26381777
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Genome-wide association study and prediction of genomic breeding values for fatty-acid composition in Korean Hanwoo cattle using a high-density single-nucleotide polymorphism array.
    Bhuiyan MSA; Kim YK; Kim HJ; Lee DH; Lee SH; Yoon HB; Lee SH
    J Anim Sci; 2018 Sep; 96(10):4063-4075. PubMed ID: 30265318
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Sharing of either phenotypes or genetic variants can increase the accuracy of genomic prediction of feed efficiency.
    Bolormaa S; MacLeod IM; Khansefid M; Marett LC; Wales WJ; Miglior F; Baes CF; Schenkel FS; Connor EE; Manzanilla-Pech CIV; Stothard P; Herman E; Nieuwhof GJ; Goddard ME; Pryce JE
    Genet Sel Evol; 2022 Sep; 54(1):60. PubMed ID: 36068488
    [TBL] [Abstract][Full Text] [Related]  

  • 26. 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; 95(7):4114-29. PubMed ID: 22720968
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits.
    Gebreyesus G; Lund MS; Buitenhuis B; Bovenhuis H; Poulsen NA; Janss LG
    Genet Sel Evol; 2017 Dec; 49(1):89. PubMed ID: 29207947
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Performances of Adaptive MultiBLUP, Bayesian regressions, and weighted-GBLUP approaches for genomic predictions in Belgian Blue beef cattle.
    Gualdrón Duarte JL; Gori AS; Hubin X; Lourenco D; Charlier C; Misztal I; Druet T
    BMC Genomics; 2020 Aug; 21(1):545. PubMed ID: 32762654
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Genomic predictions for economically important traits in Brazilian Braford and Hereford beef cattle using true and imputed genotypes.
    Piccoli ML; Brito LF; Braccini J; Cardoso FF; Sargolzaei M; Schenkel FS
    BMC Genet; 2017 Jan; 18(1):2. PubMed ID: 28100165
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Application of multivariate single-step SNP best linear unbiased predictor model and revised SNP list for genomic evaluation of dairy cattle in Australia.
    Konstantinov KV; Goddard ME
    J Dairy Sci; 2020 Sep; 103(9):8305-8316. PubMed ID: 32622609
    [TBL] [Abstract][Full Text] [Related]  

  • 31. 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; 47():99. PubMed ID: 26698091
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Genomic Prediction Using Multi-trait Weighted GBLUP Accounting for Heterogeneous Variances and Covariances Across the Genome.
    Karaman E; Lund MS; Anche MT; Janss L; Su G
    G3 (Bethesda); 2018 Nov; 8(11):3549-3558. PubMed ID: 30194089
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Genomic analysis of claw lesions in Holstein cows: Opportunities for genomic selection, quantitative trait locus detection, and gene identification.
    Croué I; Michenet A; Leclerc H; Ducrocq V
    J Dairy Sci; 2019 Jul; 102(7):6306-6318. PubMed ID: 31056323
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Prediction accuracies and genetic parameters for test-day traits from genomic and pedigree-based random regression models with or without heat stress interactions.
    Bohlouli M; Alijani S; Naderi S; Yin T; König S
    J Dairy Sci; 2019 Jan; 102(1):488-502. PubMed ID: 30343923
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Phenotypic relationships, genetic parameters, genome-wide associations, and identification of potential candidate genes for ketosis and fat-to-protein ratio in German Holstein cows.
    Klein SL; Scheper C; Brügemann K; Swalve HH; König S
    J Dairy Sci; 2019 Jul; 102(7):6276-6287. PubMed ID: 31056336
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Improving accuracy of bulls' predicted genomic breeding values for fertility using daughters' milk progesterone profiles.
    Tenghe AMM; Bouwman AC; Berglund B; de Koning DJ; Veerkamp RF
    J Dairy Sci; 2018 Jun; 101(6):5177-5193. PubMed ID: 29525306
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Genomic prediction of reproduction traits for Merino sheep.
    Bolormaa S; Brown DJ; Swan AA; van der Werf JHJ; Hayes BJ; Daetwyler HD
    Anim Genet; 2017 Jun; 48(3):338-348. PubMed ID: 28211150
    [TBL] [Abstract][Full Text] [Related]  

  • 38. 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]  

  • 39. Accuracy of prediction of genomic breeding values for residual feed intake and carcass and meat quality traits in Bos taurus, Bos indicus, and composite beef cattle.
    Bolormaa S; Pryce JE; Kemper K; Savin K; Hayes BJ; Barendse W; Zhang Y; Reich CM; Mason BA; Bunch RJ; Harrison BE; Reverter A; Herd RM; Tier B; Graser HU; Goddard ME
    J Anim Sci; 2013 Jul; 91(7):3088-104. PubMed ID: 23658330
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Design of a low-density SNP chip for the main Australian sheep breeds and its effect on imputation and genomic prediction accuracy.
    Bolormaa S; Gore K; van der Werf JH; Hayes BJ; Daetwyler HD
    Anim Genet; 2015 Oct; 46(5):544-56. PubMed ID: 26360638
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 17.