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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 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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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 |
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2023 Conference Publication Random Forest Importance Diagnostics can Capture Quantitative Genetic Properties of Markers for Genomic PredictionTomura, Shunichiro, Powell, Owen and Cooper, Mark (2023). Random Forest Importance Diagnostics can Capture Quantitative Genetic Properties of Markers for Genomic Prediction. International Congress of Genetics, Melbourne, VIC Australia, 16-21 July 2023. figShare. doi: 10.6084/m9.figshare.24211230.v1 |
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2023 Other Outputs Stochastic Simulation of Divergent Selection Experiment on a Gene-Phenotype Network: A Case Study of Shoot Branching in PlantsPowell, Owen and Cooper, Mark (2023). Stochastic Simulation of Divergent Selection Experiment on a Gene-Phenotype Network: A Case Study of Shoot Branching in Plants. figShare. (Dataset) doi: 10.6084/m9.figshare.23590083 |
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2023 Conference Publication GPU can Accelerate the Prediction of Complex PhenotypesTomura, Shunichiro, Powell, Owen and Cooper, Mark (2023). GPU can Accelerate the Prediction of Complex Phenotypes. Australasian Leadership Computing Symposium, Canberra, ACT Australia, 14-16 June 2023. doi: 10.6084/m9.figshare.24484831.v1 |
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2023 Conference Publication Hierarchical Gene-Phenotype Maps as a Framework to Predict GxExM InteractionsPowell, Owen, McLean, Greg, Brider, Jason, Technow, Frank, Tang, Tom, Messina, Carlos D., Hammer, Graeme and Cooper, Mark (2023). Hierarchical Gene-Phenotype Maps as a Framework to Predict GxExM Interactions. Quantitative Genetics and Genomics Gordon Research Conference, Ventura, CA, United States, 12-17 February 2023. |
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2023 Book Chapter Predicting Genotype × Environment × Management (G × E × M) interactions for the design of crop improvement strategies: integrating breeder, agronomist, and farmer perspectivesCooper, Mark, Messina, Carlos D., Tang, Tom, Gho, Carla, Powell, Owen M., Podlich, Dean W., Technow, Frank and Hammer, Graeme L. (2023). Predicting Genotype × Environment × Management (G × E × M) interactions for the design of crop improvement strategies: integrating breeder, agronomist, and farmer perspectives. Plant breeding reviews. (pp. 467-585) edited by Irwin Goldman. Hoboken, NJ, United States: Wiley Blackwell. doi: 10.1002/9781119874157.ch8 |
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2022 Journal Article Genomic mate-allocation strategies exploiting additive and non-additive genetic effects to maximise total clonal performance in sugarcaneYadav, Seema, Ross, Elizabeth, Wei, Xianming, Powell, Owen, Hivert, Valentin, Hickey, Lee T., Atkin, Felicity, Deomano, Emily, Aitken, Karen S., Voss-Fels, Kai P. and Hayes, Ben J. (2022). Genomic mate-allocation strategies exploiting additive and non-additive genetic effects to maximise total clonal performance in sugarcane. |
