Genomic selection in plant breeding: a comparison of models N Heslot, HP Yang, ME Sorrells, JL Jannink Crop science 52 (1), 146-160, 2012 | 739 | 2012 |
Integrating environmental covariates and crop modeling into the genomic selection framework to predict genotype by environment interactions N Heslot, D Akdemir, ME Sorrells, JL Jannink Theoretical and applied genetics 127, 463-480, 2014 | 403 | 2014 |
Training set optimization under population structure in genomic selection J Isidro, JL Jannink, D Akdemir, J Poland, N Heslot, ME Sorrells Theoretical and applied genetics 128, 145-158, 2015 | 376 | 2015 |
Perspectives for genomic selection applications and research in plants N Heslot, JL Jannink, ME Sorrells Crop Science 55 (1), 1-12, 2015 | 268 | 2015 |
Impact of marker ascertainment bias on genomic selection accuracy and estimates of genetic diversity N Heslot, J Rutkoski, J Poland, JL Jannink, ME Sorrells PloS one 8 (9), e74612, 2013 | 172 | 2013 |
The use of unbalanced historical data for genomic selection in an international wheat breeding program JC Dawson, JB Endelman, N Heslot, J Crossa, J Poland, S Dreisigacker, ... Field Crops Research 154, 12-22, 2013 | 120 | 2013 |
Using genomic prediction to characterize environments and optimize prediction accuracy in applied breeding data N Heslot, JL Jannink, ME Sorrells Crop Science 53 (3), 921-933, 2013 | 90 | 2013 |
Mapping resistance to spot blotch in a CIMMYT synthetic-derived bread wheat Z Zhu, D Bonnett, M Ellis, P Singh, N Heslot, S Dreisigacker, C Gao, ... Molecular Breeding 34, 1215-1228, 2014 | 58 | 2014 |
Evaluating grain yield in spring wheat with canopy spectral reflectance BC Bowman, J Chen, J Zhang, J Wheeler, Y Wang, W Zhao, S Nayak, ... Crop Science 55 (5), 1881-1890, 2015 | 47 | 2015 |
Characterization of Fusarium head blight resistance in a CIMMYT synthetic-derived bread wheat line Z Zhu, D Bonnett, M Ellis, X He, N Heslot, S Dreisigacker, C Gao, P Singh Euphytica 208, 367-375, 2016 | 33 | 2016 |
Optimization of selective phenotyping and population design for genomic prediction N Heslot, V Feoktistov Journal of Agricultural, Biological and Environmental Statistics 25 (4), 579-600, 2020 | 24 | 2020 |
Optimal Experimental Design of Field Trials using Differential Evolution V Feoktistov, S Pietravalle, N Heslot ArXiv, 2017 | 13 | 2017 |
An alternative covariance estimator to investigate genetic heterogeneity in populations N Heslot, JL Jannink Genetics Selection Evolution 47, 1-11, 2015 | 10 | 2015 |
Soft rule ensembles for supervised learning D Akdemir, N Heslot, JL Jannink 2013 AAAI Fall Symposium Series, 2013 | 6 | 2013 |
A method for partitioning trends in genetic mean and variance to understand breeding practices TP Oliveira, J Obšteter, I Pocrnic, N Heslot, G Gorjanc Genetics Selection Evolution 55 (1), 36, 2023 | 3 | 2023 |
IMPROVED COMPUTER IMPLEMENTED METHOD FOR PREDICTING TRUE AGRONOMICAL VALUE OF A PLANT N Heslot, S Chauvet, C Boyard, P Flament WO Patent WO2017013462A1, 2017 | 2* | 2017 |
Soft rule ensembles for statistical learning D Akdemir, N Heslot arXiv preprint arXiv:1205.4476, 2012 | 2 | 2012 |
Improved computer implemented method for breeding scheme testing S Ducrocq, N Heslot, JC Bottraud, P Flament, Z Karaman US Patent App. 16/312,971, 2019 | 1 | 2019 |
Optimal use of phenotypic data for breeding using genomic predictions ND Heslot | 1 | 2014 |
Characterization of Fusarium head blight resistance in a CIMMYT synthetic-derived bread wheat line. ZZW Zhu ZhanWang, D Bonnett, M Ellis, HXY He XinYao, N Heslot, ... | | 2016 |