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Items: 13


Usefulness Criterion and Post-selection Parental Contributions in Multi-parental Crosses: Application to Polygenic Trait Introgression.

Allier A, Moreau L, Charcosset A, Teyssèdre S, Lehermeier C.

G3 (Bethesda). 2019 May 7;9(5):1469-1479. doi: 10.1534/g3.119.400129.


Assessment of breeding programs sustainability: application of phenotypic and genomic indicators to a North European grain maize program.

Allier A, Teyssèdre S, Lehermeier C, Claustres B, Maltese S, Melkior S, Moreau L, Charcosset A.

Theor Appl Genet. 2019 May;132(5):1321-1334. doi: 10.1007/s00122-019-03280-w. Epub 2019 Jan 21.


Genetic Gain Increases by Applying the Usefulness Criterion with Improved Variance Prediction in Selection of Crosses.

Lehermeier C, Teyssèdre S, Schön CC.

Genetics. 2017 Dec;207(4):1651-1661. doi: 10.1534/genetics.117.300403. Epub 2017 Oct 16.


Genomic variance estimates: With or without disequilibrium covariances?

Lehermeier C, de Los Campos G, Wimmer V, Schön CC.

J Anim Breed Genet. 2017 Jun;134(3):232-241. doi: 10.1111/jbg.12268.


Physiological and Behavioral Responses of Dairy Cattle to the Introduction of Robot Scrapers.

Doerfler RL, Lehermeier C, Kliem H, Möstl E, Bernhardt H.

Front Vet Sci. 2016 Nov 30;3:106. eCollection 2016.


Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.).

Auinger HJ, Schönleben M, Lehermeier C, Schmidt M, Korzun V, Geiger HH, Piepho HP, Gordillo A, Wilde P, Bauer E, Schön CC.

Theor Appl Genet. 2016 Nov;129(11):2043-2053. Epub 2016 Aug 1.


Incorporating Genetic Heterogeneity in Whole-Genome Regressions Using Interactions.

de Los Campos G, Veturi Y, Vazquez AI, Lehermeier C, Pérez-Rodríguez P.

J Agric Biol Environ Stat. 2015;20(4):467-490. Epub 2015 Nov 9.


Diversity analysis and genomic prediction of Sclerotinia resistance in sunflower using a new 25 K SNP genotyping array.

Livaja M, Unterseer S, Erath W, Lehermeier C, Wieseke R, Plieske J, Polley A, Luerßen H, Wieckhorst S, Mascher M, Hahn V, Ouzunova M, Schön CC, Ganal MW.

Theor Appl Genet. 2016 Feb;129(2):317-29. doi: 10.1007/s00122-015-2629-3. Epub 2015 Nov 4.


Assessment of Genetic Heterogeneity in Structured Plant Populations Using Multivariate Whole-Genome Regression Models.

Lehermeier C, Schön CC, de Los Campos G.

Genetics. 2015 Sep;201(1):323-37. doi: 10.1534/genetics.115.177394. Epub 2015 Jun 29.


Linkage disequilibrium with linkage analysis of multiline crosses reveals different multiallelic QTL for hybrid performance in the flint and dent heterotic groups of maize.

Giraud H, Lehermeier C, Bauer E, Falque M, Segura V, Bauland C, Camisan C, Campo L, Meyer N, Ranc N, Schipprack W, Flament P, Melchinger AE, Menz M, Moreno-González J, Ouzunova M, Charcosset A, Schön CC, Moreau L.

Genetics. 2014 Dec;198(4):1717-34. doi: 10.1534/genetics.114.169367. Epub 2014 Sep 29.


Usefulness of multiparental populations of maize (Zea mays L.) for genome-based prediction.

Lehermeier C, Krämer N, Bauer E, Bauland C, Camisan C, Campo L, Flament P, Melchinger AE, Menz M, Meyer N, Moreau L, Moreno-González J, Ouzunova M, Pausch H, Ranc N, Schipprack W, Schönleben M, Walter H, Charcosset A, Schön CC.

Genetics. 2014 Sep;198(1):3-16. doi: 10.1534/genetics.114.161943.


Genome-wide prediction of traits with different genetic architecture through efficient variable selection.

Wimmer V, Lehermeier C, Albrecht T, Auinger HJ, Wang Y, Schön CC.

Genetics. 2013 Oct;195(2):573-87. doi: 10.1534/genetics.113.150078. Epub 2013 Aug 9.


Sensitivity to prior specification in Bayesian genome-based prediction models.

Lehermeier C, Wimmer V, Albrecht T, Auinger HJ, Gianola D, Schmid VJ, Schön CC.

Stat Appl Genet Mol Biol. 2013 Jun;12(3):375-91. doi: 10.1515/sagmb-2012-0042.


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