Genomic prediction ability for yield-related traits in German winter barley elite material

[1]  Kevin P. Smith,et al.  Genomic Selection Performs Similarly to Phenotypic Selection in Barley , 2016 .

[2]  J. Zhao,et al.  Correction: The Impact of Genetic Relationship and Linkage Disequilibrium on Genomic Selection , 2016, PloS one.

[3]  A. Graner,et al.  Prediction of malting quality traits in barley based on genome-wide marker data to assess the potential of genomic selection , 2016, Theoretical and Applied Genetics.

[4]  Bruce S Weir,et al.  Model-free Estimation of Recent Genetic Relatedness. , 2016, American journal of human genetics.

[5]  Mihaela M. Martis,et al.  Assessing the Barley Genome Zipper and Genomic Resources for Breeding Purposes , 2015, The plant genome.

[6]  R. Kleespies,et al.  Investigation on pathogenic antagonists of selected insect pests – an overview , 2015 .

[7]  Tuong-Vi Cao,et al.  Accuracy of Genomic Selection in a Rice Synthetic Population Developed for Recurrent Selection Breeding , 2015, PloS one.

[8]  Yurii B. Shvetsov,et al.  Common Genetic Variation In Cellular Transport Genes and Epithelial Ovarian Cancer (EOC) Risk , 2015, PloS one.

[9]  T. Günther,et al.  Genome‐wide association studies in elite varieties of German winter barley using single‐marker and haplotype‐based methods , 2015 .

[10]  Kevin P. Smith,et al.  Assessing Genomic Selection Prediction Accuracy in a Dynamic Barley Breeding Population , 2015, The plant genome.

[11]  J. Poland,et al.  Training set optimization under population structure in genomic selection , 2014, Theoretical and Applied Genetics.

[12]  H. Piepho,et al.  The importance of phenotypic data analysis for genomic prediction - a case study comparing different spatial models in rye , 2014, BMC Genomics.

[13]  G. de los Campos,et al.  Genome-Wide Regression and Prediction with the BGLR Statistical Package , 2014, Genetics.

[14]  Gary J. Muehlbauer,et al.  The USDA Barley Core Collection: Genetic Diversity, Population Structure, and Potential for Genome-Wide Association Studies , 2014, PloS one.

[15]  Zhanyou Xu,et al.  The impact of population structure on genomic prediction in stratified populations , 2014, Theoretical and Applied Genetics.

[16]  N. Cogan,et al.  StAMPP: an R package for calculation of genetic differentiation and structure of mixed‐ploidy level populations , 2013, Molecular ecology resources.

[17]  R. Fernando,et al.  Genomic BLUP Decoded: A Look into the Black Box of Genomic Prediction , 2013, Genetics.

[18]  M. Calus,et al.  Whole-Genome Regression and Prediction Methods Applied to Plant and Animal Breeding , 2013, Genetics.

[19]  M. Calus,et al.  The Effect of Linkage Disequilibrium and Family Relationships on the Reliability of Genomic Prediction , 2013, Genetics.

[20]  Paul D. Shaw,et al.  Natural variation in a homolog of Antirrhinum CENTRORADIALIS contributed to spring growth habit and environmental adaptation in cultivated barley , 2012, Nature Genetics.

[21]  Hans-Peter Piepho,et al.  A stage‐wise approach for the analysis of multi‐environment trials , 2012, Biometrical journal. Biometrische Zeitschrift.

[22]  Jose Crossa,et al.  Effectiveness of Genomic Prediction of Maize Hybrid Performance in Different Breeding Populations and Environments , 2012, G3: Genes | Genomes | Genetics.

[23]  J H J van der Werf,et al.  Components of the accuracy of genomic prediction in a multi-breed sheep population. , 2012, Journal of animal science.

[24]  Gustavo de los Campos,et al.  Inferences from Genomic Models in Stratified Populations , 2012, Genetics.

[25]  Chris-Carolin Schön,et al.  synbreed: a framework for the analysis of genomic prediction data using R , 2012, Bioinform..

[26]  W. Friedt,et al.  Identification of marker-trait associations in the German winter barley breeding gene pool (Hordeum vulgare L.) , 2012, Molecular Breeding.

[27]  Kevin P. Smith,et al.  Potential and Optimization of Genomic Selection for Fusarium Head Blight Resistance in Six-Row Barley , 2012 .

[28]  K. Tamura,et al.  The development of highly transferable intron-spanning markers for temperate forage grasses , 2012, Molecular Breeding.

[29]  Thibaut Jombart,et al.  adegenet 1.3-1: new tools for the analysis of genome-wide SNP data , 2011, Bioinform..

[30]  H. Iwata,et al.  Accuracy of Genomic Selection Prediction in Barley Breeding Programs: A Simulation Study Based On the Real Single Nucleotide Polymorphism Data of Barley Breeding Lines , 2011 .

[31]  W. Beavis,et al.  Accuracy and Training Population Design for Genomic Selection on Quantitative Traits in Elite North American Oats , 2011 .

[32]  Jean-Luc Jannink,et al.  Genomic Selection Accuracy using Multifamily Prediction Models in a Wheat Breeding Program , 2011 .

[33]  S. Ceccarelli,et al.  Barley Breeding History, Progress, Objectives, and Technology , 2010 .

[34]  Iwan Supit,et al.  Recent changes in the climatic yield potential of various crops in Europe , 2010 .

[35]  J. Woolliams,et al.  The Impact of Genetic Architecture on Genome-Wide Evaluation Methods , 2010, Genetics.

[36]  Jean-Luc Jannink,et al.  Genomic selection in plant breeding: from theory to practice. , 2010, Briefings in functional genomics.

[37]  Timothy J. Close,et al.  Population Structure and Linkage Disequilibrium in U.S. Barley Germplasm: Implications for Association Mapping , 2010 .

[38]  Trevor Hastie,et al.  Regularization Paths for Generalized Linear Models via Coordinate Descent. , 2010, Journal of statistical software.

[39]  H. Piepho,et al.  Comparison of Weighting in Two‐Stage Analysis of Plant Breeding Trials , 2009 .

[40]  H. Piepho.  Ridge Regression and Extensions for Genomewide Selection in Maize , 2009 .

[41]  S. Ceccarelli,et al.  Patterns of genetic diversity and linkage disequilibrium in a highly structured Hordeum vulgare association-mapping population for the Mediterranean basin , 2009, Theoretical and Applied Genetics.

[42]  Jean-Luc Jannink,et al.  Factors Affecting Accuracy From Genomic Selection in Populations Derived From Multiple Inbred Lines: A Barley Case Study , 2009, Genetics.

[43]  R. Bernardo.  Molecular Markers and Selection for Complex Traits in Plants: Learning from the Last 20 Years , 2008 .

[44]  Noah A Rosenberg,et al.  Mathematical properties of the r2 measure of linkage disequilibrium. , 2008, Theoretical population biology.

[45]  M. Goddard,et al.  Linkage Disequilibrium and Persistence of Phase in Holstein–Friesian, Jersey and Angus Cattle , 2008, Genetics.

[46]  Thibaut Jombart,et al.  adegenet: a R package for the multivariate analysis of genetic markers , 2008, Bioinform..

[47]  S. Ceccarelli,et al.  Mapping adaptation of barley to droughted environments , 2008, Euphytica.

[48]  Jonathan H. Crouch,et al.  Marker-Assisted Selection in Plant Breeding: From Publications to Practice , 2008 .

[49]  E. Mazzucotelli,et al.  Drought tolerance improvement in crop plants: An integrated view from breeding to genomics , 2008 .

[50]  R. Fernando,et al.  The Impact of Genetic Relationship Information on Genome-Assisted Breeding Values , 2007, Genetics.

[51]  B. Browning,et al.  Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. , 2007, American journal of human genetics.

[52]  H. Piepho,et al.  Computing Heritability and Selection Response From Unbalanced Plant Breeding Trials , 2007, Genetics.

[53]  Anne-Béatrice Dufour,et al.  The ade4 Package: Implementing the Duality Diagram for Ecologists , 2007 .

[54]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[55]  M. Ganal,et al.  Temporal trends of genetic diversity in European barley cultivars (Hordeum vulgare L.) , 2007, Molecular Breeding.

[56]  Brian R. Cullis,et al.  On the design of early generation variety trials with correlated data , 2006 .

[57]  M. Sorrells,et al.  Association Mapping of Kernel Size and Milling Quality in Wheat (Triticum aestivum L.) Cultivars , 2006, Genetics.

[58]  W. Köhler,et al.  Molecular assessment of genetic diversity in winter barley and its use in breeding , 2005, Euphytica.

[59]  D. McKenney,et al.  Potential impacts of climate change on corn, soybeans and barley yields in Atlantic Canada , 2005 .

[60]  H. Zou,et al.  Regularization and variable selection via the elastic net , 2005 .

[61]  E. Pang,et al.  An introduction to markers, quantitative trait loci (QTL) mapping and marker-assisted selection for crop improvement: The basic concepts , 2005, Euphytica.

[62]  P. Morrell,et al.  Low levels of linkage disequilibrium in wild barley (Hordeum vulgare ssp. spontaneum) despite high rates of self-fertilization. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[63]  Shumpei Niida,et al.  Estrogen Regulates the Production of VEGF for Osteoclast Formation and Activity in op/op Mice , 2003, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[64]  A. Jahoor,et al.  RFLP diversity within and between major groups of barley in Europe , 2003 .

[65]  M. Goddard,et al.  Prediction of total genetic value using genome-wide dense marker maps. , 2001, Genetics.

[66]  Brian R. Cullis,et al.  Spatial analysis of field experiments : an extension to two dimensions , 1991 .

[67]  R. Lande,et al.  Efficiency of marker-assisted selection in the improvement of quantitative traits. , 1990, Genetics.

[68]  B. Weir,et al.  ESTIMATING F‐STATISTICS FOR THE ANALYSIS OF POPULATION STRUCTURE , 1984, Evolution; international journal of organic evolution.

[69]  S. R. Searle,et al.  The estimation of environmental and genetic trends from records subject to culling. , 1959 .

[70]  R. Varshney,et al.  Genomic Selection for Crop Improvement , 2017, Springer International Publishing.

[71]  K. Schmid,et al.  Genomic Selection in Barley Breeding , 2014 .

[72]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[73]  P. Pérez,et al.  BGLR: A Statistical Package for Whole Genome Regression and Prediction , 2013 .

[74]  Hsiao-Pei Yang,et al.  Genomic Selection in Plant Breeding: A Comparison of Models , 2012 .

[75]  B. Cullis,et al.  mixed models for S language environments ASReml-R reference manual ASReml estimates variance components under a general linear mixed model by residual maximum likelihood (REML) , 2009 .

[76]  Andy Liaw,et al.  Classification and Regression by randomForest , 2007 .

[77]  L. Breiman.  Random Forests , 2001, Machine Learning.

[78]  S. Pichyangkul,et al.  Monocyte Activation by Porphyromonas gingivalis LPS in Aggressive Periodontitis with the Use of Whole-blood Cultures , 2004 .

[79]  R. Tibshirani.  Regression Shrinkage and Selection via the Lasso , 1996 .

[80]  C. R. Henderson.  Applications of linear models in animal breeding , 1984 .