DiffBreed: automatic differentiation enables efficient gradient-based optimization of breeding strategies
The proposed automatic differentiation framework was implemented as the Python module "DiffBreed." This module and all the scripts used in this study, including the gradient-based optimization, are available from the "KosukeHamazaki/GORA-PT" repository on GitHub, https://github.com/KosukeHamazaki/GORA-PT. While the simulated datasets in the present study are available from the same repository, the optimized results by PyTorch were not shared in this repository due to the file sizes. Instead, all datasets, including the optimized ones, will be shared in the repository on Zenodo, https://doi.org/10.5281/zenodo.14046522.
Authors
- Kosuke Hamazaki (ORCID: https://orcid.org/0000-0002-7486-7438)
- Koji Tsuda (ORCID: https://orcid.org/0000-0002-4288-1606)
- Hiroyoshi Iwata (ORCID: https://orcid.org/0000-0002-6747-7036)
Institutions
- RIKEN Center for Advanced Intelligence Project (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- Bioinformatics
- Published
- 2025-10-22
- DOI
- https://doi.org/10.1093/bioinformatics/btaf586
- Primary Topic
- Evolutionary Algorithms and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- ACT-X