| Crop breeding for a changing climate: Integrating phenomics and genomics with bioinformatics JI Marsh, H Hu, M Gill, J Batley, D Edwards Theoretical and Applied Genetics 134, 1677-1690, 2021 | 73 | 2021 |
| Plant genotype to phenotype prediction using machine learning MF Danilevicz, M Gill, R Anderson, J Batley, M Bennamoun, PE Bayer, ... Frontiers in Genetics 13, 822173, 2022 | 57 | 2022 |
| Machine learning models outperform deep learning models, provide interpretation and facilitate feature selection for soybean trait prediction M Gill, R Anderson, H Hu, M Bennamoun, J Petereit, B Valliyodan, ... BMC plant biology 22 (1), 180, 2022 | 46 | 2022 |
| Pangenomes as a resource to accelerate breeding of under-utilised crop species CG Tay Fernandez, BJ Nestor, MF Danilevicz, M Gill, J Petereit, PE Bayer, ... International Journal of Molecular Sciences 23 (5), 2671, 2022 | 24 | 2022 |
| DNABERT-based explainable lncRNA identification in plant genome assemblies MF Danilevicz, M Gill, CGT Fernandez, J Petereit, SR Upadhyaya, ... Computational and Structural Biotechnology Journal 21, 5676-5685, 2023 | 7 | 2023 |
| An SGSGeneloss-based method for constructing a gene presence–absence table using mosdepth CG Tay Fernandez, JI Marsh, BJ Nestor, M Gill, AA Golicz, PE Bayer, ... Plant Comparative Genomics, 73-80, 2022 | 7 | 2022 |
| Producing high-quality single nucleotide polymorphism data for genome-wide association studies PE Bayer, M Gill, MF Danilevicz, D Edwards Genome-Wide Association Studies, 153-159, 2022 | 4 | 2022 |
