1559 related articles for article (PubMed ID: 28836943)
1. An efficient unified model for genome-wide association studies and genomic selection.
Li H; Su G; Jiang L; Bao Z
Genet Sel Evol; 2017 Aug; 49(1):64. PubMed ID: 28836943
[TBL] [Abstract][Full Text] [Related]
2. Using markers with large effect in genetic and genomic predictions.
Lopes MS; Bovenhuis H; van Son M; Nordbø Ø; Grindflek EH; Knol EF; Bastiaansen JW
J Anim Sci; 2017 Jan; 95(1):59-71. PubMed ID: 28177367
[TBL] [Abstract][Full Text] [Related]
3. Prediction of genomic breeding values based on pre-selected SNPs using ssGBLUP, WssGBLUP and BayesB for Edwardsiellosis resistance in Japanese flounder.
Lu S; Liu Y; Yu X; Li Y; Yang Y; Wei M; Zhou Q; Wang J; Zhang Y; Zheng W; Chen S
Genet Sel Evol; 2020 Aug; 52(1):49. PubMed ID: 32811444
[TBL] [Abstract][Full Text] [Related]
4. Comparative analysis of the GBLUP, emBayesB, and GWAS algorithms to predict genetic values in large yellow croaker (Larimichthys crocea).
Dong L; Xiao S; Wang Q; Wang Z
BMC Genomics; 2016 Jun; 17():460. PubMed ID: 27301965
[TBL] [Abstract][Full Text] [Related]
5. Accuracy of genomic selection for a sib-evaluated trait using identity-by-state and identity-by-descent relationships.
Vela-Avitúa S; Meuwissen TH; Luan T; Ødegård J
Genet Sel Evol; 2015 Feb; 47(1):9. PubMed ID: 25888184
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Multiple-trait QTL mapping and genomic prediction for wool traits in sheep.
Bolormaa S; Swan AA; Brown DJ; Hatcher S; Moghaddar N; van der Werf JH; Goddard ME; Daetwyler HD
Genet Sel Evol; 2017 Aug; 49(1):62. PubMed ID: 28810834
[TBL] [Abstract][Full Text] [Related]
8. GWABLUP: genome-wide association assisted best linear unbiased prediction of genetic values.
Meuwissen T; Eikje LS; Gjuvsland AB
Genet Sel Evol; 2024 Mar; 56(1):17. PubMed ID: 38429665
[TBL] [Abstract][Full Text] [Related]
9. 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; 18(1):121. PubMed ID: 28143402
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. On the use of whole-genome sequence data for across-breed genomic prediction and fine-scale mapping of QTL.
Meuwissen T; van den Berg I; Goddard M
Genet Sel Evol; 2021 Feb; 53(1):19. PubMed ID: 33637049
[TBL] [Abstract][Full Text] [Related]
12. Use of gene expression and whole-genome sequence information to improve the accuracy of genomic prediction for carcass traits in Hanwoo cattle.
de Las Heras-Saldana S; Lopez BI; Moghaddar N; Park W; Park JE; Chung KY; Lim D; Lee SH; Shin D; van der Werf JHJ
Genet Sel Evol; 2020 Sep; 52(1):54. PubMed ID: 32993481
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Efficient weighting methods for genomic best linear-unbiased prediction (BLUP) adapted to the genetic architectures of quantitative traits.
Ren D; An L; Li B; Qiao L; Liu W
Heredity (Edinb); 2021 Feb; 126(2):320-334. PubMed ID: 32980863
[TBL] [Abstract][Full Text] [Related]
15. Genome-wide association mapping and genomic prediction of agronomical traits and breeding values in Iranian wheat under rain-fed and well-watered conditions.
Rabieyan E; Bihamta MR; Moghaddam ME; Mohammadi V; Alipour H
BMC Genomics; 2022 Dec; 23(1):831. PubMed ID: 36522726
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Genomic Prediction Accuracy of Seven Breeding Selection Traits Improved by QTL Identification in Flax.
Lan S; Zheng C; Hauck K; McCausland M; Duguid SD; Booker HM; Cloutier S; You FM
Int J Mol Sci; 2020 Feb; 21(5):. PubMed ID: 32106624
[TBL] [Abstract][Full Text] [Related]
18. Random forest estimation of genomic breeding values for disease susceptibility over different disease incidences and genomic architectures in simulated cow calibration groups.
Naderi S; Yin T; König S
J Dairy Sci; 2016 Sep; 99(9):7261-7273. PubMed ID: 27344385
[TBL] [Abstract][Full Text] [Related]
19. Comparison of genomic predictions using genomic relationship matrices built with different weighting factors to account for locus-specific variances.
Su G; Christensen OF; Janss L; Lund MS
J Dairy Sci; 2014 Oct; 97(10):6547-59. PubMed ID: 25129495
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]