| Support vector machine regression for the prediction of maize hybrid performance S Maenhout, B De Baets, G Haesaert, E Van Bockstaele Theoretical and applied genetics 115, 1003-1013, 2007 | 78 | 2007 |
| Needles: toward large-scale genomic prediction with marker-by-environment interaction A De Coninck, B De Baets, D Kourounis, F Verbosio, O Schenk, ... Genetics 203 (1), 543-555, 2016 | 63 | 2016 |
| Prediction of maize single-cross hybrid performance: support vector machine regression versus best linear prediction S Maenhout, B De Baets, G Haesaert Theoretical and applied genetics 120, 415-427, 2010 | 47 | 2010 |
| Graph-based data selection for the construction of genomic prediction models S Maenhout, B De Baets, G Haesaert Genetics 185 (4), 1463-1475, 2010 | 22 | 2010 |
| Preservation of genetic variation in a breeding population for long-term genetic gain D Vanavermaete, J Fostier, S Maenhout, B De Baets G3: Genes, Genomes, Genetics 10 (8), 2753-2762, 2020 | 18 | 2020 |
| Marker-based estimation of the coefficient of coancestry in hybrid breeding programmes S Maenhout, B De Baets, G Haesaert Theoretical and applied genetics 118, 1181-1192, 2009 | 18 | 2009 |
| DAIRRy-BLUP: A high-performance computing approach to genomic prediction AD Coninck, J Fostier, S Maenhout, B De Baets Genetics 197 (3), 813-822, 2014 | 16 | 2014 |
| Marker-based screening of maize inbred lines using support vector machine regression S Maenhout, B De Baets, G Haesaert, E Van Bockstaele Euphytica 161, 123-131, 2008 | 13 | 2008 |
| CoCoa: a software tool for estimating the coefficient of coancestry from multilocus genotype data S Maenhout, B De Baets, G Haesaert Bioinformatics 25 (20), 2753-2754, 2009 | 11 | 2009 |
| Towards parallel large-scale genomic prediction by coupling sparse and dense matrix algebra A De Coninck, D Kourounis, F Verbosio, O Schenk, B De Baets, ... 2015 23rd Euromicro International Conference on Parallel, Distributed, and …, 2015 | 8 | 2015 |
| Deep scoping: a breeding strategy to preserve, reintroduce and exploit genetic variation D Vanavermaete, J Fostier, S Maenhout, B De Baets Theoretical and Applied Genetics 134 (12), 3845-3861, 2021 | 7 | 2021 |
| Intercropping indices evaluation on grain legume-small grain cereals mixture: a critical meta-analysis review R Zustovi, S Landschoot, K Dewitte, G Verlinden, R Dubey, S Maenhout, ... Agronomy for Sustainable Development 44 (1), 5, 2024 | 5 | 2024 |
| Cereal-legume intercropping: a smart review using topic modelling S Landschoot, R Zustovi, K Dewitte, NP Randall, S Maenhout, G Haesaert Frontiers in Plant Science 14, 1228850, 2024 | 3 | 2024 |
| Adaptive scoping: balancing short-and long-term genetic gain in plant breeding D Vanavermaete, J Fostier, S Maenhout, B De Baets Euphytica 218 (8), 109, 2022 | 1 | 2022 |
| Effects of Variety Type and Maturity at Harvest on Whole Crop Maize Silage Characteristics J Latre, E Wambacq, J de Boever, D de Brabander, S Maenhout, B Deroo, ... FORAGE CONSERVATION, 2010 | 1 | 2010 |
| Harnessing monocrop breeding strategies for intercrops R Dubey, R Zustovi, S Landschoot, K Dewitte, G Verlinden, G Haesaert, ... Frontiers in Plant Science 15, 1394413, 2024 | | 2024 |
| Genome-wide association study for in vitro digestibility and related traits in triticale forage A De Zutter, MC Piro, S Maenhout, HP Maurer, J De Boever, H Muylle, ... BMC Plant Biology 24 (1), 223, 2024 | | 2024 |
| Oracle selection provides insight into how far off practice is from Utopia in plant breeding D Vanavermaete, S Maenhout, J Fostier, B De Baets Frontiers in Plant Science 14, 1218665, 2023 | | 2023 |
| Including explicit marker-by-environment interaction for large-scale genomic prediction A De Coninck, D Kourounis, F Verbosio, O Schenk, B De Baets, ... 20th National symposium on Applied Biological Sciences 80 (1), 117-121, 2015 | | 2015 |
| A high performance computing approach for genomic prediction A De Coninck, J Fostier, S Maenhout, B De Baets 19th National symposium on Applied Biological Sciences 79 (1), 115-119, 2014 | | 2014 |
