Architectural good practices for reproducible benchmarking in protein machine learning
- DOI
- 10.3389/fbinf.2026.1925740
- Published
- 2026-09-08
- Container
- Frontiers in Bioinformatics
- Publisher
- Frontiers Media SA
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3389/fbinf.2026.1925740,
title = {Architectural good practices for reproducible benchmarking in protein machine learning},
author = {Julián García-Vinuesa and Diego Fernández-Villegas and Michelle Soto-García and Xavier Cadet and Mehdi D. Davari and Frederic Cadet and Juan A. Asenjo and Roberto Uribe-Paredes and David Medina-Ortiz},
year = {2026},
journal = {Frontiers in Bioinformatics},
doi = {10.3389/fbinf.2026.1925740},
url = {https://doi.org/10.3389/fbinf.2026.1925740}
}RIS
TY - JOUR TI - Architectural good practices for reproducible benchmarking in protein machine learning AU - Julián García-Vinuesa AU - Diego Fernández-Villegas AU - Michelle Soto-García AU - Xavier Cadet AU - Mehdi D. Davari AU - Frederic Cadet AU - Juan A. Asenjo AU - Roberto Uribe-Paredes AU - David Medina-Ortiz PY - 2026 JO - Frontiers in Bioinformatics DO - 10.3389/fbinf.2026.1925740 UR - https://doi.org/10.3389/fbinf.2026.1925740 ER -
APA
García-Vinuesa, J., Fernández-Villegas, D., Soto-García, M., Cadet, X., Davari, M. D., Cadet, F., Asenjo, J. A., Uribe-Paredes, R., & Medina-Ortiz, D. (2026). Architectural good practices for reproducible benchmarking in protein machine learning. Frontiers in Bioinformatics. https://doi.org/10.3389/fbinf.2026.1925740
Source records
- crossref · retrieved 2026-09-25T02:14:45.275Z