Quantifying genomic connectedness and prediction accuracy from additive and non-additive gene actions

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Quantifying genomic connectedness and prediction accuracy from additive and non-additive gene actions

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наукова стаття, опублікована у вересні 2018

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Quantifying genomic connectedn ...... and non-additive gene actions

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Quantifying genomic connectedn ...... and non-additive gene actions

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Quantifying genomic connectedn ...... and non-additive gene actions

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Quantifying genomic connectedn ...... and non-additive gene actions

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Quantifying genomic connectedn ...... and non-additive gene actions

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Quantifying genomic connectedn ...... and non-additive gene actions

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Quantifying genomic connectedn ...... and non-additive gene actions

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P2093

Mehdi Momen

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P2860

Prediction of total genetic value using genome-wide dense marker maps

On epistasis: why it is unimportant in polygenic directional selection

Genomic prediction of crossbred performance based on purebred Landrace and Yorkshire data using a dominance model.

Parametric and nonparametric statistical methods for genomic selection of traits with additive and epistatic genetic architectures

Epistasis and its contribution to genetic variance components.

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

The importance of information on relatives for the prediction of genomic breeding values and the implications for the makeup of reference data sets in livestock breeding schemes

Predicting complex traits using a diffusion kernel on genetic markers with an application to dairy cattle and wheat data

A common dataset for genomic analysis of livestock populations

Maximizing the reliability of genomic selection by optimizing the calibration set of reference individuals: comparison of methods in two diverse groups of maize inbreds (Zea mays L.).

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s12711-018-0415-9

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scholarly article

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10.1186/S12711-018-0415-9

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English

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P478

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P50

Gota Morota

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2018-09-17T00:00:00Z

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1107066612

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30223766

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6142710

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