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Germany

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Employment (2)

RAGT SA: Druelle, Midi-Pyrénées, FR

2017-09-15 to present | Research Scientist (Genetics & Analytics Unit)
Employment
Source: Self-asserted source
Christina Lehermeier

Technical University Munich: Freising, DE

2011-10-01 to 2017-08-31 | Research Scientist (Plant Breeding)
Employment
Source: Self-asserted source
Christina Lehermeier

Works (16)

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

Theoretical and Applied Genetics
2019 | Journal article
Source: Self-asserted source
Christina Lehermeier

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

G3: Genes, Genomes, Genetics
2019 | Journal article
Source: Self-asserted source
Christina Lehermeier

Improving Short- and Long-Term Genetic Gain by Accounting for Within-Family Variance in Optimal Cross-Selection

Frontiers in Genetics
2019-10-29 | Journal article
Part of ISSN: 1664-8021
Source: Self-asserted source
Christina Lehermeier

Genomic prediction with a maize collaborative panel: identification of genetic resources to enrich elite breeding programs

Theoretical and Applied Genetics
2019-10-08 | Journal article
Part of ISSN: 0040-5752
Part of ISSN: 1432-2242
Source: Self-asserted source
Christina Lehermeier

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

Genetics
2017 | Journal article
ARXIV:

http://www.genetics.org/content/207/4/1651.full.pdf

Source: Self-asserted source
Christina Lehermeier

Genomic variance estimates: With or without disequilibrium covariances?

J. Anim. Breed. Genet.
2017-06 | Journal article
Source: Self-asserted source
Christina Lehermeier

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

Theor. Appl. Genet.
2016 | Journal article
Source: Self-asserted source
Christina Lehermeier

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

Theor. Appl. Genet.
2016 | Journal article
Source: Self-asserted source
Christina Lehermeier

Physiological and behavioral responses of dairy cattle to the introduction of robot scrapers

Front Vet Sci
2016 | Journal article
Source: Self-asserted source
Christina Lehermeier

Incorporating genetic heterogeneity in whole-genome regressions using interactions

J. Agric. Biol. Envir. S.
2015-12 | Journal article
Source: Self-asserted source
Christina Lehermeier

Assessment of genetic heterogeneity in structured plant populations using multivariate whole-genome regression models

Genetics
2015-09 | Journal article
Source: Self-asserted source
Christina Lehermeier

Efficiency of variable selection in genome-wide prediction for traits of different genetic architecture

10th World Congress of Genetics Applied to Livestock Production
2014 | Conference paper
Source: Self-asserted source
Christina Lehermeier

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

Genetics
2014-12 | Journal article
Source: Self-asserted source
Christina Lehermeier

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

Genetics
2014-09 | Journal article
Source: Self-asserted source
Christina Lehermeier

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

Genetics
2013-10 | Journal article
Source: Self-asserted source
Christina Lehermeier

Sensitivity to prior specification in Bayesian genome-based prediction models

Stat. Appl. Genet. Mol. Biol.
2013-01 | Journal article
Source: Self-asserted source
Christina Lehermeier