Federated learning for the pathogenicity annotation of genetic variants in multi-site clinical settings
All source code required to reproduce the results presented in this article, implemented in Python, is available under the GNU General Public License v3 at https://github.com/RausellLab/FedLearnVar.
Authors
- Antonio Rausell (ORCID: https://orcid.org/0000-0002-4832-6101)
- Emidio Capriotti (ORCID: https://orcid.org/0000-0002-2323-0963)
- Francisco Requena Silvente (ORCID: https://orcid.org/0000-0003-1043-0277)
- Nigreisy Montalvo (ORCID: https://orcid.org/0009-0007-4361-5821)
Institutions
- Inserm (FR)
- Université Paris Cité (FR)
- Cornell University (US)
- Lander Institute (IL)
- Assistance Publique – Hôpitaux de Paris (FR)
- Center for Genomic Science (IT)
- Génétique Médicale & Génomique Fonctionelle (FR)
- Institut des Maladies Génétiques Imagine (FR)
- University of Bologna (IT)
Publication Details
- Journal
- Bioinformatics
- Published
- 2025-09-19
- DOI
- https://doi.org/10.1093/bioinformatics/btaf523
- Citations
- 1
- Primary Topic
- Genomics and Rare Diseases
- Type
- article
- Field-Weighted Citation Impact
- 1.82