419 related articles for article (PubMed ID: 26947266)
1. Smooth-Threshold Multivariate Genetic Prediction with Unbiased Model Selection.
Ueki M; Tamiya G;
Genet Epidemiol; 2016 Apr; 40(3):233-43. PubMed ID: 26947266
[TBL] [Abstract][Full Text] [Related]
2. Whole-genome sequence-based genomic prediction in laying chickens with different genomic relationship matrices to account for genetic architecture.
Ni G; Cavero D; Fangmann A; Erbe M; Simianer H
Genet Sel Evol; 2017 Jan; 49(1):8. PubMed ID: 28093063
[TBL] [Abstract][Full Text] [Related]
3. Genome-wide prediction using Bayesian additive regression trees.
Waldmann P
Genet Sel Evol; 2016 Jun; 48(1):42. PubMed ID: 27286957
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. A Multiple-Trait Bayesian Lasso for Genome-Enabled Analysis and Prediction of Complex Traits.
Gianola D; Fernando RL
Genetics; 2020 Feb; 214(2):305-331. PubMed ID: 31879318
[TBL] [Abstract][Full Text] [Related]
6. A novel genomic selection method combining GBLUP and LASSO.
Li H; Wang J; Bao Z
Genetica; 2015 Jun; 143(3):299-304. PubMed ID: 25655266
[TBL] [Abstract][Full Text] [Related]
7. Predictive performance of genomic selection methods for carcass traits in Hanwoo beef cattle: impacts of the genetic architecture.
Mehrban H; Lee DH; Moradi MH; IlCho C; Naserkheil M; Ibáñez-Escriche N
Genet Sel Evol; 2017 Jan; 49(1):1. PubMed ID: 28093066
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Detecting genetic association through shortest paths in a bidirected graph.
Ueki M; Kawasaki Y; Tamiya G;
Genet Epidemiol; 2017 Sep; 41(6):481-497. PubMed ID: 28626864
[TBL] [Abstract][Full Text] [Related]
10. Efficient Implementation of Penalized Regression for Genetic Risk Prediction.
Privé F; Aschard H; Blum MGB
Genetics; 2019 May; 212(1):65-74. PubMed ID: 30808621
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. 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]
13. Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.
Nguyen TT; Huang J; Wu Q; Nguyen T; Li M
BMC Genomics; 2015; 16 Suppl 2(Suppl 2):S5. PubMed ID: 25708662
[TBL] [Abstract][Full Text] [Related]
14. Fast score test with global null estimation regardless of missing genotypes.
Sato S; Ueki M;
PLoS One; 2018; 13(7):e0199692. PubMed ID: 29975732
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. Penalized multimarker vs. single-marker regression methods for genome-wide association studies of quantitative traits.
Yi H; Breheny P; Imam N; Liu Y; Hoeschele I
Genetics; 2015 Jan; 199(1):205-22. PubMed ID: 25354699
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Reliabilities of Genomic Prediction for Young Stock Survival Traits Using 54K SNP Chip Augmented With Additional Single-Nucleotide Polymorphisms Selected From Imputed Whole-Genome Sequencing Data.
Gebreyesus G; Lund MS; Sahana G; Su G
Front Genet; 2021; 12():667300. PubMed ID: 34349779
[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. Powerful and Adaptive Testing for Multi-trait and Multi-SNP Associations with GWAS and Sequencing Data.
Kim J; Zhang Y; Pan W;
Genetics; 2016 Jun; 203(2):715-31. PubMed ID: 27075728
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]