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.).
about
Fortune telling: metabolic markers of plant performanceData-driven encoding for quantitative genetic trait prediction.Prediction of malting quality traits in barley based on genome-wide marker data to assess the potential of genomic selection.Recovering power in association mapping panels with variable levels of linkage disequilibrium.Evaluating Methods of Updating Training Data in Long-Term Genomewide SelectionIntraspecific variation of recombination rate in maize.Usefulness of multiparental populations of maize (Zea mays L.) for genome-based prediction.A powerful tool for genome analysis in maize: development and evaluation of the high density 600 k SNP genotyping array.Variable-Selection Emerges on Top in Empirical Comparison of Whole-Genome Complex-Trait Prediction Methods.The genetic architecture of maize stalk strength.Training set optimization under population structure in genomic selection.Optimization of genomic selection training populations with a genetic algorithmIntegrating Crop Growth Models with Whole Genome Prediction through Approximate Bayesian Computation.Association mapping for cold tolerance in two large maize inbred panels.On the Accuracy of Genomic Selection.Does encoding matter? A novel view on the quantitative genetic trait prediction problem.Using Genetic Distance to Infer the Accuracy of Genomic PredictionImprovement of Predictive Ability by Uniform Coverage of the Target Genetic Space.Numerous genetic loci identified for drought tolerance in the maize nested association mapping populations.Genomic Prediction in Pea: Effect of Marker Density and Training Population Size and Composition on Prediction Accuracy.Accuracy of Genomic Prediction in Switchgrass (Panicum virgatum L.) Improved by Accounting for Linkage DisequilibriumEfficient Breeding by Genomic Mating.Genomic prediction contributing to a promising global strategy to turbocharge gene banks.Genomic Relatedness Strengthens Genetic Connectedness Across Management UnitsPatterns of Genetic Structure and Linkage Disequilibrium in a Large Collection of Pea Germplasm.Accuracy of Genomic Prediction in Synthetic Populations Depending on the Number of Parents, Relatedness, and Ancestral Linkage Disequilibrium.Accuracy of genomic breeding values revisited: Assessment of two established approaches and a novel one to determine the accuracy in two-step genomic prediction.Genomic selection prediction accuracy in a perennial crop: case study of oil palm (Elaeis guineensis Jacq.).Genomic assisted selection for enhancing line breeding: merging genomic and phenotypic selection in winter wheat breeding programs with preliminary yield trials.Genetic variation of growth dynamics in maize (Zea mays L.) revealed through automated non-invasive phenotyping.Novel applications of multitask learning and multiple output regression to multiple genetic trait prediction.Genomic selection in a commercial winter wheat population.Genomic selection across multiple breeding cycles in applied bread wheat breedingGenome properties and prospects of genomic prediction of hybrid performance in a breeding program of maize.Predicting genomic selection efficiency to optimize calibration set and to assess prediction accuracy in highly structured populations.Genomic preselection with genotyping-by-sequencing increases performance of commercial oil palm hybrid crosses.Genomic Prediction Within and Across Biparental Families: Means and Variances of Prediction Accuracy and Usefulness of Deterministic Equations.Goals and hurdles for a successful implementation of genomic selection in breeding programme for selected annual and perennial crops.Dent and Flint maize diversity panels reveal important genetic potential for increasing biomass production.An analytical framework to derive the expected precision of genomic selection.
P2860
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P2860
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.).
description
2012 nî lūn-bûn
@nan
2012年の論文
@ja
2012年学术文章
@wuu
2012年学术文章
@zh-cn
2012年学术文章
@zh-hans
2012年学术文章
@zh-my
2012年学术文章
@zh-sg
2012年學術文章
@yue
2012年學術文章
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2012年學術文章
@zh-hant
name
Maximizing the reliability of ...... f maize inbreds (Zea mays L.).
@ast
Maximizing the reliability of ...... f maize inbreds (Zea mays L.).
@en
type
label
Maximizing the reliability of ...... f maize inbreds (Zea mays L.).
@ast
Maximizing the reliability of ...... f maize inbreds (Zea mays L.).
@en
prefLabel
Maximizing the reliability of ...... f maize inbreds (Zea mays L.).
@ast
Maximizing the reliability of ...... f maize inbreds (Zea mays L.).
@en
P2093
P2860
P50
P1433
P1476
Maximizing the reliability of ...... f maize inbreds (Zea mays L.).
@en
P2093
C Giauffret
C-C Schoen
J Moreno-Gonzalez
P2860
P304
P356
10.1534/GENETICS.112.141473
P407
P577
2012-08-03T00:00:00Z