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2025 Journal Article Improved Genomic Prediction Performance with Ensembles of Diverse ModelsTomura, Shunichiro, Wilkinson, Melanie J., Cooper, Mark and Powell, Owen (2025). Improved Genomic Prediction Performance with Ensembles of Diverse Models. G3: Genes, Genomes, Genetics, 15 (5) jkaf048, 1-15. doi: 10.1093/g3journal/jkaf048 |
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2024 Journal Article Potential approaches to create ultimate genotypes in crops and livestockHayes, Ben J., Mahony, Timothy J., Villiers, Kira, Warburton, Christie, Kemper, Kathryn E., Dinglasan, Eric, Robinson, Hannah, Powell, Owen, Voss-Fels, Kai, Godwin, Ian D. and Hickey, Lee T. (2024). Potential approaches to create ultimate genotypes in crops and livestock. Nature Genetics, 56 (11), 2310-2317. doi: 10.1038/s41588-024-01942-0 |
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2023 Journal Article Extending the breeder’s equation to take aim at the target population of environmentsCooper, Mark, Powell, Owen, Gho Brito, Carla, Tang, Tom and Messina, Carlos (2023). Extending the breeder’s equation to take aim at the target population of environments. Frontiers in Plant Science, 14 1129591, 1-10. doi: 10.3389/fpls.2023.1129591 |
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2022 Journal Article Investigations into the emergent properties of gene-to-phenotype networks across cycles of selection: a case study of shoot branching in plantsPowell, Owen M., Barbier, Francois, Voss-Fels, Kai P., Beveridge, Christine and Cooper, Mark (2022). Investigations into the emergent properties of gene-to-phenotype networks across cycles of selection: a case study of shoot branching in plants. in silico Plants, 4 (1) diac006, 1-9. doi: 10.1093/insilicoplants/diac006 |
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2026 Journal Article Genetic linkage map of the Australian barramundi (Lates calcarifer) reveals potential to leverage extreme sex-specific recombination and sequential hermaphrodism for ultimate breeding program controlHintzsche, Jessica, Bertola, Lorenzo V., Jones, David B., Warburton, Christie, Powell, Owen, Ross, Elizabeth M., Harrison, Paul, Cate, Holly S., Jerry, Dean R., Hayes, Ben J. and Zenger, Kyall R. (2026). Genetic linkage map of the Australian barramundi (Lates calcarifer) reveals potential to leverage extreme sex-specific recombination and sequential hermaphrodism for ultimate breeding program control. Aquaculture, 622 744046, 744046. doi: 10.1016/j.aquaculture.2026.744046 |
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2026 Journal Article Optimisation of Weighted Ensembles of Genomic Prediction Models in MaizeTomura, Shunichiro, Powell, Owen, Wilkinson, Melanie J, Lefvre, James and Cooper, Mark (2026). Optimisation of Weighted Ensembles of Genomic Prediction Models in Maize. in silico Plants diag010. doi: 10.1093/insilicoplants/diag010 |
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2026 Journal Article Ensemble-based genomic prediction for maize flowering-time improves prediction accuracy and reveals novel insights into trait genetic variationTomura, Shunichiro, Powell, Owen, Wilkinson, Melanie J and Cooper, Mark (2026). Ensemble-based genomic prediction for maize flowering-time improves prediction accuracy and reveals novel insights into trait genetic variation. G3: Genes, Genomes, Genetics jkag090. doi: 10.1093/g3journal/jkag090 |
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2026 Journal Article Simulating the impact of recombination rate on genomic selection breeding outcomesBoyny, Zsa Zsa, Lester, Nicholas, Massel, Karen, Powell, Owen, Snowdon, Rod and Weber, Sven (2026). Simulating the impact of recombination rate on genomic selection breeding outcomes. G3: Genes, Genomes, Genetics jkag049. doi: 10.1093/g3journal/jkag049 |
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2025 Journal Article Ensemble AnalySis with Interpretable Genomic Prediction (EasiGP): Computational tool for interpreting ensembles of genomic prediction modelsTomura, Shunichiro, Wilkinson, Melanie J., Powell, Owen and Cooper, Mark (2025). Ensemble AnalySis with Interpretable Genomic Prediction (EasiGP): Computational tool for interpreting ensembles of genomic prediction models. The Plant Genome, 18 (4) e70138, 1-16. doi: 10.1002/tpg2.70138 |
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2025 Journal Article Breeding perspectives on tackling trait genome-to-phenome (G2P) dimensionality using ensemble-based genomic predictionCooper, Mark, Tomura, Shunichiro, Wilkinson, Melanie J., Powell, Owen and Messina, Carlos D. (2025). Breeding perspectives on tackling trait genome-to-phenome (G2P) dimensionality using ensemble-based genomic prediction. Theoretical and Applied Genetics, 138 (7) 172, 1-24. doi: 10.1007/s00122-025-04960-6 |
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2024 Other Outputs Improvements in prediction performance of ensemble approaches for genomic prediction in crop breedingTomura, Shunichiro, Cooper, Mark and Powell, Owen (2024). Improvements in prediction performance of ensemble approaches for genomic prediction in crop breeding. doi: 10.1101/2024.09.06.611589 |
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2024 Conference Publication Prediction of non-additive genetic effects with hierarchical genomic prediction modelsPowell, Owen, McLean, Greg, Brider, Jason, Saddigh, Joe, Technow, Frank, Tang, Tom, Totir, Radu, Messina, Carlos D., Hammer, Graeme and Cooper, Mark (2024). Prediction of non-additive genetic effects with hierarchical genomic prediction models. International Conference of Quantitative Genetics (ICQG) 7, Vienna, Austria, 22-26 July 2024. doi: 10.6084/m9.figshare.26425735.v1 |
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2024 Journal Article Genomic prediction for sugarcane diseases including hybrid Bayesian-machine learning approachesChen, Chensong, Bhuiyan, Shamsul A., Ross, Elizabeth, Powell, Owen, Dinglasan, Eric, Wei, Xianming, Atkin, Felicity, Deomano, Emily and Hayes, Ben (2024). Genomic prediction for sugarcane diseases including hybrid Bayesian-machine learning approaches. Frontiers in Plant Science, 15 1398903, 1-13. doi: 10.3389/fpls.2024.1398903 |
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2024 Journal Article Adaptation and plasticity of yield in hybrid and inbred sorghumOtwani, Daniel, Hunt, Colleen, Cruickshank, Alan, Powell, Owen, Koltunow, Anna, Mace, Emma and Jordan, David (2024). Adaptation and plasticity of yield in hybrid and inbred sorghum. Crop Science, 64 (2), 560-570. doi: 10.1002/csc2.21160 |
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2023 Journal Article Use of continuous genotypes for genomic prediction in sugarcaneYadav, Seema, Ross, Elizabeth M., Wei, Xianming, Liu, Shouye, Nguyen, Loan To, Powell, Owen, Hickey, Lee T., Deomano, Emily, Atkin, Felicity, Voss‐Fels, Kai P. and Hayes, Ben J. (2023). Use of continuous genotypes for genomic prediction in sugarcane. The Plant Genome, 17 (1) e20417, e20417. doi: 10.1002/tpg2.20417 |
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2023 Journal Article Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategiesYadav, Seema, Ross, Elizabeth M., Wei, Xianming, Powell, Owen, Hivert, Valentin, Hickey, Lee T., Atkin, Felicity, Deomano, Emily, Aitken, Karen S., Voss-Fels, Kai P. and Hayes, Ben J. (2023). Optimising clonal performance in sugarcane: leveraging non-additive effects via mate-allocation strategies. Frontiers in Plant Science, 14 1260517, 1260517. doi: 10.3389/fpls.2023.1260517 |
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2023 Conference Publication APSIM-WGP: a software platform to predict crop GxExM interactionsPowell, Owen, McLean, Greg, Brider, Jason, Hammer, Graeme and Cooper, Mark (2023). APSIM-WGP: a software platform to predict crop GxExM interactions. GxExM Symposium II, Gainesville, FL USA, 6-7 November 2023. |
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2023 Journal Article Comparison of genomic prediction models for general combining ability in early stages of hybrid breeding programsde Jong, Guilherme, Powell, Owen, Gorjanc, Gregor, Hickey, John M. and Gaynor, R. Chris (2023). Comparison of genomic prediction models for general combining ability in early stages of hybrid breeding programs. Crop Science, 63 (6), 3338-3355. doi: 10.1002/csc2.21105 |
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2023 Journal Article Genomic prediction with machine learning in sugarcane, a complex highly polyploid clonally propagated crop with substantial non‐additive variation for key traitsChen, Chensong, Powell, Owen, Dinglasan, Eric, Ross, Elizabeth M., Yadav, Seema, Wei, Xianming, Atkin, Felicity, Deomano, Emily and Hayes, Ben J. (2023). Genomic prediction with machine learning in sugarcane, a complex highly polyploid clonally propagated crop with substantial non‐additive variation for key traits. The Plant Genome, 16 (4) e20390, 1-13. doi: 10.1002/tpg2.20390 |
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2023 Journal Article Advancing artificial intelligence to help feed the worldHayes, Ben J., Chen, Chensong, Powell, Owen, Dinglasan, Eric, Villiers, Kira, Kemper, Kathryn E. and Hickey, Lee T. (2023). Advancing artificial intelligence to help feed the world. Nature Biotechnology, 41 (9), 1-2. doi: 10.1038/s41587-023-01898-2 |
