Dimension reduction and variable selection for genomic selection: application to predicting milk yield in Holsteins.
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A comparison of principal component regression and genomic REML for genomic prediction across populationsWhole-genome regression and prediction methods applied to plant and animal breedingAccuracy of Genomic Prediction in Switchgrass (Panicum virgatum L.) Improved by Accounting for Linkage DisequilibriumEnlarging a training set for genomic selection by imputation of un-genotyped animals in populations of varying genetic architecture.Multiple-breed genomic evaluation by principal component analysis in small size populations.Use of different statistical models to predict direct genomic values for productive and functional traits in Italian Holsteins.Exploring the areas of applicability of whole-genome prediction methods for Asian rice (Oryza sativa L.).Supervised independent component analysis as an alternative method for genomic selection in pigsUse of principal component approach to predict direct genomic breeding values for beef traits in Italian Simmental cattle1Incorporating Prior Knowledge of Principal Components in Genomic Prediction
P2860
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P2860
Dimension reduction and variable selection for genomic selection: application to predicting milk yield in Holsteins.
description
2011 nî lūn-bûn
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2011年学术文章
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name
Dimension reduction and variab ...... cting milk yield in Holsteins.
@en
Dimension reduction and variab ...... cting milk yield in Holsteins.
@nl
type
label
Dimension reduction and variab ...... cting milk yield in Holsteins.
@en
Dimension reduction and variab ...... cting milk yield in Holsteins.
@nl
prefLabel
Dimension reduction and variab ...... cting milk yield in Holsteins.
@en
Dimension reduction and variab ...... cting milk yield in Holsteins.
@nl
P2093
P2860
P1476
Dimension reduction and variab ...... cting milk yield in Holsteins.
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P2093
P2860
P304
P356
10.1111/J.1439-0388.2011.00917.X
P577
2011-03-28T00:00:00Z