Clifti-GPT: privacy-preserving federated fine-tuning and transferable inference of foundation models on clinical single-cell data.

Bakhtiari M, Elkjaer ML, Can AO, Theis F, Oubounyt M, Baumbach J

Open source

DOI
10.1186/s13040-026-00582-w
Published
2026 Aug 5
Container
BioData mining
Publisher
Not recorded
Open access
yes

Credibility signals

limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.1186/s13040-026-00582-w,
  title = {Clifti-GPT: privacy-preserving federated fine-tuning and transferable inference of foundation models on clinical single-cell data.},
  author = {Bakhtiari M and Elkjaer ML and Can AO and Theis F and Oubounyt M and Baumbach J},
  year = {2026},
  journal = {BioData mining},
  doi = {10.1186/s13040-026-00582-w},
  url = {https://doi.org/10.1186/s13040-026-00582-w}
}

RIS

TY  - JOUR
TI  - Clifti-GPT: privacy-preserving federated fine-tuning and transferable inference of foundation models on clinical single-cell data.
AU  - Bakhtiari M
AU  - Elkjaer ML
AU  - Can AO
AU  - Theis F
AU  - Oubounyt M
AU  - Baumbach J
PY  - 2026
JO  - BioData mining
DO  - 10.1186/s13040-026-00582-w
UR  - https://doi.org/10.1186/s13040-026-00582-w
ER  - 

APA

M, B., ML, E., AO, C., F, T., M, O., & J, B. (2026). Clifti-GPT: privacy-preserving federated fine-tuning and transferable inference of foundation models on clinical single-cell data.. BioData mining. https://doi.org/10.1186/s13040-026-00582-w

Source records