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Items: 1 to 20 of 353

1.

Estimating additive and non-additive genetic variances and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers.

Su G, Christensen OF, Ostersen T, Henryon M, Lund MS.

PLoS One. 2012;7(9):e45293. doi: 10.1371/journal.pone.0045293. Epub 2012 Sep 13.

2.

Genome-Enabled Estimates of Additive and Nonadditive Genetic Variances and Prediction of Apple Phenotypes Across Environments.

Kumar S, Molloy C, Muñoz P, Daetwyler H, Chagné D, Volz R.

G3 (Bethesda). 2015 Oct 23;5(12):2711-8. doi: 10.1534/g3.115.021105.

3.

GVCBLUP: a computer package for genomic prediction and variance component estimation of additive and dominance effects.

Wang C, Prakapenka D, Wang S, Pulugurta S, Runesha HB, Da Y.

BMC Bioinformatics. 2014 Aug 9;15:270. doi: 10.1186/1471-2105-15-270.

4.

Genomic analysis of dominance effects on milk production and conformation traits in Fleckvieh cattle.

Ertl J, Legarra A, Vitezica ZG, Varona L, Edel C, Emmerling R, Götz KU.

Genet Sel Evol. 2014 Jun 24;46:40. doi: 10.1186/1297-9686-46-40.

5.

Mixed model methods for genomic prediction and variance component estimation of additive and dominance effects using SNP markers.

Da Y, Wang C, Wang S, Hu G.

PLoS One. 2014 Jan 30;9(1):e87666. doi: 10.1371/journal.pone.0087666. eCollection 2014.

6.

Improvement of prediction ability for genomic selection of dairy cattle by including dominance effects.

Sun C, VanRaden PM, Cole JB, O'Connell JR.

PLoS One. 2014 Aug 1;9(8):e103934. doi: 10.1371/journal.pone.0103934. eCollection 2014.

7.

Non-additive genetic variation in growth, carcass and fertility traits of beef cattle.

Bolormaa S, Pryce JE, Zhang Y, Reverter A, Barendse W, Hayes BJ, Goddard ME.

Genet Sel Evol. 2015 Apr 2;47:26. doi: 10.1186/s12711-015-0114-8.

8.

Including non-additive genetic effects in Bayesian methods for the prediction of genetic values based on genome-wide markers.

Wittenburg D, Melzer N, Reinsch N.

BMC Genet. 2011 Aug 25;12:74. doi: 10.1186/1471-2156-12-74.

9.

Estimation of Additive, Dominance, and Imprinting Genetic Variance Using Genomic Data.

Lopes MS, Bastiaansen JW, Janss L, Knol EF, Bovenhuis H.

G3 (Bethesda). 2015 Oct 4;5(12):2629-37. doi: 10.1534/g3.115.019513.

10.

Predicting genetic values: a kernel-based best linear unbiased prediction with genomic data.

Ober U, Erbe M, Long N, Porcu E, Schlather M, Simianer H.

Genetics. 2011 Jul;188(3):695-708. doi: 10.1534/genetics.111.128694. Epub 2011 Apr 21.

11.

Using the realized relationship matrix to disentangle confounding factors for the estimation of genetic variance components of complex traits.

Lee SH, Goddard ME, Visscher PM, van der Werf JH.

Genet Sel Evol. 2010 Jun 15;42:22. doi: 10.1186/1297-9686-42-22.

12.

A comparison of five methods to predict genomic breeding values of dairy bulls from genome-wide SNP markers.

Moser G, Tier B, Crump RE, Khatkar MS, Raadsma HW.

Genet Sel Evol. 2009 Dec 31;41:56. doi: 10.1186/1297-9686-41-56.

13.

On the additive and dominant variance and covariance of individuals within the genomic selection scope.

Vitezica ZG, Varona L, Legarra A.

Genetics. 2013 Dec;195(4):1223-30. doi: 10.1534/genetics.113.155176. Epub 2013 Oct 11.

14.

Including dominance effects in the genomic BLUP method for genomic evaluation.

Nishio M, Satoh M.

PLoS One. 2014 Jan 8;9(1):e85792. doi: 10.1371/journal.pone.0085792. eCollection 2014.

15.

Modeling additive and non-additive effects in a hybrid population using genome-wide genotyping: prediction accuracy implications.

Bouvet JM, Makouanzi G, Cros D, Vigneron P.

Heredity (Edinb). 2016 Feb;116(2):146-57. doi: 10.1038/hdy.2015.78. Epub 2015 Sep 2.

PMID:
26328760
16.
17.

Unraveling additive from nonadditive effects using genomic relationship matrices.

Muñoz PR, Resende MF Jr, Gezan SA, Resende MD, de Los Campos G, Kirst M, Huber D, Peter GF.

Genetics. 2014 Dec;198(4):1759-68. doi: 10.1534/genetics.114.171322. Epub 2014 Oct 15.

18.

Integrating Nonadditive Genomic Relationship Matrices into the Study of Genetic Architecture of Complex Traits.

Nazarian A, Gezan SA.

J Hered. 2016 Mar;107(2):153-62. doi: 10.1093/jhered/esv096. Epub 2015 Dec 27.

PMID:
26712858
19.

Invited review: Genomic selection in dairy cattle: progress and challenges.

Hayes BJ, Bowman PJ, Chamberlain AJ, Goddard ME.

J Dairy Sci. 2009 Feb;92(2):433-43. doi: 10.3168/jds.2008-1646. Review. Erratum in: J Dairy Sci. 2009 Mar;92(3):1313.

PMID:
19164653
20.

Validation of markers with non-additive effects on milk yield and fertility in Holstein and Jersey cows.

Aliloo H, Pryce JE, González-Recio O, Cocks BG, Hayes BJ.

BMC Genet. 2015 Jul 22;16:89. doi: 10.1186/s12863-015-0241-9.

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