160 related articles for article (PubMed ID: 23134637)
21. Efficiency of genomic selection using Bayesian multi-marker models for traits selected to reflect a wide range of heritabilities and frequencies of detected quantitative traits loci in mice.
Kapell DN; Sorensen D; Su G; Janss LL; Ashworth CJ; Roehe R
BMC Genet; 2012 May; 13():42. PubMed ID: 22651804
[TBL] [Abstract][Full Text] [Related]
22. Predicting Growth Traits with Genomic Selection Methods in Zhikong Scallop (Chlamys farreri).
Wang Y; Sun G; Zeng Q; Chen Z; Hu X; Li H; Wang S; Bao Z
Mar Biotechnol (NY); 2018 Dec; 20(6):769-779. PubMed ID: 30116982
[TBL] [Abstract][Full Text] [Related]
23. Cassava yield traits predicted by genomic selection methods.
Andrade LRB; Sousa MBE; Oliveira EJ; Resende MDV; Azevedo CF
PLoS One; 2019; 14(11):e0224920. PubMed ID: 31725759
[TBL] [Abstract][Full Text] [Related]
24. 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]
25. Exploring the areas of applicability of whole-genome prediction methods for Asian rice (Oryza sativa L.).
Onogi A; Ideta O; Inoshita Y; Ebana K; Yoshioka T; Yamasaki M; Iwata H
Theor Appl Genet; 2015 Jan; 128(1):41-53. PubMed ID: 25341369
[TBL] [Abstract][Full Text] [Related]
26. Different models of genetic variation and their effect on genomic evaluation.
Clark SA; Hickey JM; van der Werf JH
Genet Sel Evol; 2011 May; 43(1):18. PubMed ID: 21575265
[TBL] [Abstract][Full Text] [Related]
27. Genomic dissection of additive and non-additive genetic effects and genomic prediction in an open-pollinated family test of Japanese larch.
Dong L; Xie Y; Zhang Y; Wang R; Sun X
BMC Genomics; 2024 Jan; 25(1):11. PubMed ID: 38166605
[TBL] [Abstract][Full Text] [Related]
28. Genomic prediction of simulated multibreed and purebred performance using observed fifty thousand single nucleotide polymorphism genotypes.
Kizilkaya K; Fernando RL; Garrick DJ
J Anim Sci; 2010 Feb; 88(2):544-51. PubMed ID: 19820059
[TBL] [Abstract][Full Text] [Related]
29. Empirical and deterministic accuracies of across-population genomic prediction.
Wientjes YC; Veerkamp RF; Bijma P; Bovenhuis H; Schrooten C; Calus MP
Genet Sel Evol; 2015 Feb; 47(1):5. PubMed ID: 25885467
[TBL] [Abstract][Full Text] [Related]
30. 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]
31. 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]
32. Accuracy of pedigree and genomic predictions of carcass and novel meat quality traits in multi-breed sheep data assessed by cross-validation.
Daetwyler HD; Swan AA; van der Werf JH; Hayes BJ
Genet Sel Evol; 2012 Nov; 44(1):33. PubMed ID: 23146144
[TBL] [Abstract][Full Text] [Related]
33. 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]
34. 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]
35. Genomic prediction with parallel computing for slaughter traits in Chinese Simmental beef cattle using high-density genotypes.
Guo P; Zhu B; Xu L; Niu H; Wang Z; Guan L; Liang Y; Ni H; Guo Y; Chen Y; Zhang L; Gao X; Gao H; Li J
PLoS One; 2017; 12(7):e0179885. PubMed ID: 28723906
[TBL] [Abstract][Full Text] [Related]
36. 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]
37. Genome-enabled methods for predicting litter size in pigs: a comparison.
Tusell L; Pérez-Rodríguez P; Forni S; Wu XL; Gianola D
Animal; 2013 Nov; 7(11):1739-49. PubMed ID: 23880322
[TBL] [Abstract][Full Text] [Related]
38. 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]
39. Genome-enabled prediction of reproductive traits in Nellore cattle using parametric models and machine learning methods.
Alves AAC; Espigolan R; Bresolin T; Costa RM; Fernandes Júnior GA; Ventura RV; Carvalheiro R; Albuquerque LG
Anim Genet; 2021 Feb; 52(1):32-46. PubMed ID: 33191532
[TBL] [Abstract][Full Text] [Related]
40. 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]
[Previous] [Next] [New Search]
