Prediction accuracies of GEBV across EM iterations in the first validation generation.

Performance of the best solutions post-evaluated for 500 validation episodes for experiments in which NEE is varied from 1 to 1000.

Paolo Pagliuca (5532746)
Stefano Nolfi (3141294)

March 2019

F is set to 1.0 (i.e. the ENV matrix is re-generated every generation). Each number indicate the ave...

Summary of simulated datasets and scenarios.

Xiaochen Sun (120336)
Long Qu (120340)
Dorian J. Garrick (120342)
Jack C. M. Dekkers (120344)
Rohan L. Fernando (120349)

November 2012

Scenarios differed in training data size, number of chromosomes, number of QTL, and whether the g...

Accuracy of genomic breeding values (GEBVs) using 5 different approaches.

Zhe Zhang (81603)
Jianfeng Liu (122580)
Xiangdong Ding (122577)
Piter Bijma (153734)
Dirk-Jan de Koning (57294)
Qin Zhang (58638)

February 2013

The graph shows the correlation between estimated and true breeding values in generations 2–6 usi...

Accuracy of GEBV and regression coefficient of TBV on GEBV in the first validation generation of Dataset A for GBLUP, BayesA, BayesB and fastBayesA.

Xiaochen Sun (120336)
Long Qu (120340)
Dorian J. Garrick (120342)
Jack C. M. Dekkers (120344)
Rohan L. Fernando (120349)

November 2012

1. Heterogeneous genetic variance of QTL.2. Constant genetic variance of QTL.3. Mea...

Accuracy of GEBVs for different simulated QTL numbers in generation 2 (h2 = 0.5).

Zhe Zhang (81603)
Jianfeng Liu (122580)
Xiangdong Ding (122577)
Piter Bijma (153734)
Dirk-Jan de Koning (57294)
Qin Zhang (58638)

February 2013

Accuracy of GEBVs for different simulated QTL numbers in generation 2 (h2 = 0.5...

Accuracy of GEBVs for different heritability in generation 2 (Nqtl = 50).

Zhe Zhang (81603)
Jianfeng Liu (122580)
Xiangdong Ding (122577)
Piter Bijma (153734)
Dirk-Jan de Koning (57294)
Qin Zhang (58638)

February 2013

Accuracy of GEBVs for different heritability in generation 2 (Nqtl = 50).</p

Model performance on test set.

Santiago A. Cadena (6622961)
George H. Denfield (6622964)
Edgar Y. Walker (6622967)
Leon A. Gatys (6622970)
Andreas S. Tolias (391696)
Matthias Bethge (146851)
Alexander S. Ecker (391694)

April 2019

Average fraction of explainable variance explained (FEV) for models using different VGG layers as no...

Accuracies of GEBVs for the two traits in generation 3 in four scenarios of different genetic correlations.

Chonglong Wang (3584984)
Xiujin Li (2160691)
Rong Qian (2413783)
Guosheng Su (307770)
Qin Zhang (58638)
Xiangdong Ding (122577)

April 2017

Accuracies of GEBVs for the two traits in generation 3 in four scenarios of different genetic cor...

Predictive accuracies of GEBVs estimated using GBLUP and six Bayesian methods in generations 2–6 with a population size = 1000, QTL = 200, h2 = 0.5.

Bo Zhu (118038)
Miao Zhu (680090)
Jicai Jiang (122571)
Hong Niu (2637253)
Yanhui Wang (108090)
Yang Wu (66682)
Lingyang Xu (389143)
Yan Chen (4308)
Lupei Zhang (647384)
Xue Gao (237216)
Huijiang Gao (628320)
Jianfeng Liu (122580)
Junya Li (240083)

May 2016

Predictive accuracies of GEBVs estimated using GBLUP and six Bayesian methods in generations 2–6 ...

Prediction abilities (Pearson correlation coefficient between the GEBV and phenotypes) based on five fold cross-validation in the rice dataset.

Boby Mathew (1473064)
Jens Léon (3148986)
Mikko J. Sillanpää (133635)

July 2018

Prediction abilities (Pearson correlation coefficient between the GEBV and phenotypes) based on f...

Fig 8 -

Muhammad Naqeeb Nawaz (13899283)
Sana Ullah Qamar (13899286)
Badee Alshameri (13899289)
Muhammad Muneeb Nawaz (13899292)
Waqas Hassan (13899295)
Tariq Ahmed Awan (13899298)

October 2022

Performance assessment of prediction model based on different criteria; (a) comparison of statistica...

Prediction abilities (Pearson correlation coefficient between the GEBV and phenotypes) based on five fold cross-validation in the maize dataset.

Boby Mathew (1473064)
Jens Léon (3148986)
Mikko J. Sillanpää (133635)

July 2018

Prediction abilities (Pearson correlation coefficient between the GEBV and phenotypes) based on f...

Mean correlation between GEBV obtained by cross validation of the training data set (Yp) and the observed BLUP values of the validation data sets (Yo).

Cécile Grenier (788754)
Tuong-Vi Cao (788755)
Yolima Ospina (788756)
Constanza Quintero (731953)
Marc Henri Châtel (788757)
Joe Tohme (40985)
Brigitte Courtois (68582)
Nourollah Ahmadi (480013)

August 2015

Results presented for 2 traits, 9 incidence matrices and 3 k-fold cross validation experiments.</...

Performance of the best solutions post-evaluated for 500 validation episodes for experiments in which the environmental conditions vary with different frequency across generations.

Paolo Pagliuca (5532746)
Stefano Nolfi (3141294)

March 2019

F = 1 / G, where G is the number of generations after which the environmental conditions vary. Exper...

Data from: Factors affecting GEBV accuracy with single-step Bayesian models

Zhou, Lei
Mrode, Raphael
Zhang, Shengli
Zhang, Qin
Li, Bugao
Liu, Jian-Feng

September 2017

A single-step approach to obtain genomic prediction was firstly proposed in 2009. Many studies have ...

Performance of the best solutions post-evaluated for 500 validation episodes for experiments in which NEE is varied from 1 to 1000.

Paolo Pagliuca (5532746)
Stefano Nolfi (3141294)

March 2019

F is set to 1.0 (i.e. the ENV matrix is re-generated every generation). Each number indicate the ave...

Summary of simulated datasets and scenarios.

Xiaochen Sun (120336)
Long Qu (120340)
Dorian J. Garrick (120342)
Jack C. M. Dekkers (120344)
Rohan L. Fernando (120349)

November 2012

Scenarios differed in training data size, number of chromosomes, number of QTL, and whether the g...

Accuracy of genomic breeding values (GEBVs) using 5 different approaches.

Zhe Zhang (81603)
Jianfeng Liu (122580)
Xiangdong Ding (122577)
Piter Bijma (153734)
Dirk-Jan de Koning (57294)
Qin Zhang (58638)

February 2013

The graph shows the correlation between estimated and true breeding values in generations 2–6 usi...

Accuracy of GEBV and regression coefficient of TBV on GEBV in the first validation generation of Dataset A for GBLUP, BayesA, BayesB and fastBayesA.

Xiaochen Sun (120336)
Long Qu (120340)
Dorian J. Garrick (120342)
Jack C. M. Dekkers (120344)
Rohan L. Fernando (120349)

November 2012

1. Heterogeneous genetic variance of QTL.2. Constant genetic variance of QTL.3. Mea...

Accuracy of GEBVs for different simulated QTL numbers in generation 2 (h2 = 0.5).

Zhe Zhang (81603)
Jianfeng Liu (122580)
Xiangdong Ding (122577)
Piter Bijma (153734)
Dirk-Jan de Koning (57294)
Qin Zhang (58638)

February 2013

Accuracy of GEBVs for different simulated QTL numbers in generation 2 (h2 = 0.5...

Accuracy of GEBVs for different heritability in generation 2 (Nqtl = 50).

Zhe Zhang (81603)
Jianfeng Liu (122580)
Xiangdong Ding (122577)
Piter Bijma (153734)
Dirk-Jan de Koning (57294)
Qin Zhang (58638)

February 2013

Accuracy of GEBVs for different heritability in generation 2 (Nqtl = 50).</p

Model performance on test set.

Santiago A. Cadena (6622961)
George H. Denfield (6622964)
Edgar Y. Walker (6622967)
Leon A. Gatys (6622970)
Andreas S. Tolias (391696)
Matthias Bethge (146851)
Alexander S. Ecker (391694)

April 2019

Average fraction of explainable variance explained (FEV) for models using different VGG layers as no...

Accuracies of GEBVs for the two traits in generation 3 in four scenarios of different genetic correlations.

Chonglong Wang (3584984)
Xiujin Li (2160691)
Rong Qian (2413783)
Guosheng Su (307770)
Qin Zhang (58638)
Xiangdong Ding (122577)

April 2017

Accuracies of GEBVs for the two traits in generation 3 in four scenarios of different genetic cor...

Predictive accuracies of GEBVs estimated using GBLUP and six Bayesian methods in generations 2–6 with a population size = 1000, QTL = 200, h2 = 0.5.

Bo Zhu (118038)
Miao Zhu (680090)
Jicai Jiang (122571)
Hong Niu (2637253)
Yanhui Wang (108090)
Yang Wu (66682)
Lingyang Xu (389143)
Yan Chen (4308)
Lupei Zhang (647384)
Xue Gao (237216)
Huijiang Gao (628320)
Jianfeng Liu (122580)
Junya Li (240083)

May 2016

Predictive accuracies of GEBVs estimated using GBLUP and six Bayesian methods in generations 2–6 ...

Prediction abilities (Pearson correlation coefficient between the GEBV and phenotypes) based on five fold cross-validation in the rice dataset.

Boby Mathew (1473064)
Jens Léon (3148986)
Mikko J. Sillanpää (133635)

July 2018

Prediction abilities (Pearson correlation coefficient between the GEBV and phenotypes) based on f...

Fig 8 -

Muhammad Naqeeb Nawaz (13899283)
Sana Ullah Qamar (13899286)
Badee Alshameri (13899289)
Muhammad Muneeb Nawaz (13899292)
Waqas Hassan (13899295)
Tariq Ahmed Awan (13899298)

October 2022

Performance assessment of prediction model based on different criteria; (a) comparison of statistica...

Prediction abilities (Pearson correlation coefficient between the GEBV and phenotypes) based on five fold cross-validation in the maize dataset.

Boby Mathew (1473064)
Jens Léon (3148986)
Mikko J. Sillanpää (133635)

July 2018

Prediction abilities (Pearson correlation coefficient between the GEBV and phenotypes) based on f...

Mean correlation between GEBV obtained by cross validation of the training data set (Yp) and the observed BLUP values of the validation data sets (Yo).

Cécile Grenier (788754)
Tuong-Vi Cao (788755)
Yolima Ospina (788756)
Constanza Quintero (731953)
Marc Henri Châtel (788757)
Joe Tohme (40985)
Brigitte Courtois (68582)
Nourollah Ahmadi (480013)

August 2015

Results presented for 2 traits, 9 incidence matrices and 3 k-fold cross validation experiments.</...

Performance of the best solutions post-evaluated for 500 validation episodes for experiments in which the environmental conditions vary with different frequency across generations.

Paolo Pagliuca (5532746)
Stefano Nolfi (3141294)

March 2019

F = 1 / G, where G is the number of generations after which the environmental conditions vary. Exper...

Data from: Factors affecting GEBV accuracy with single-step Bayesian models

Zhou, Lei
Mrode, Raphael
Zhang, Shengli
Zhang, Qin
Li, Bugao
Liu, Jian-Feng

September 2017

A single-step approach to obtain genomic prediction was firstly proposed in 2009. Many studies have ...

Performance of the best solutions post-evaluated for 500 validation episodes for experiments in which NEE is varied from 1 to 1000.

Paolo Pagliuca (5532746)
Stefano Nolfi (3141294)

March 2019

F is set to 1.0 (i.e. the ENV matrix is re-generated every generation). Each number indicate the ave...

Summary of simulated datasets and scenarios.

Xiaochen Sun (120336)
Long Qu (120340)
Dorian J. Garrick (120342)
Jack C. M. Dekkers (120344)
Rohan L. Fernando (120349)

November 2012

Scenarios differed in training data size, number of chromosomes, number of QTL, and whether the g...

Accuracy of genomic breeding values (GEBVs) using 5 different approaches.

Zhe Zhang (81603)
Jianfeng Liu (122580)
Xiangdong Ding (122577)
Piter Bijma (153734)
Dirk-Jan de Koning (57294)
Qin Zhang (58638)

February 2013

The graph shows the correlation between estimated and true breeding values in generations 2–6 usi...

Prediction accuracies of GEBV across EM iterations in the first validation generation.

Abstract

Extracted data

Topics

Prediction accuracies of GEBV across EM iterations in the first validation generation.

Abstract

Extracted data

Topics

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