scBERT
Single-cell foundation model, published as a pretrained deep language model for cell type annotation (reference 4); not designed for perturbation prediction and used here with a linear decoder (main text paragraph 2).
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- scBERT (Ahlmann-Eltze et al. 2025) Configuration · configuration · 4 evaluations · 8 results
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Evidence
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Sources and history
Release 2026-10-22-1b7cf027e4f6 · Record review: source checked
1 source record and release history
- Deep-learning-based gene perturbation effect prediction does not yet outperform simple linear baselines · Original source · Nature Methods 22(8):1657, published online 2025-08-04; PMC12328236 full-text XML
Technical metadata and extraction receipts
Stable ID: perturbation-ahlmann-20261011-model-scbert
- areas
- cells-tissues; single-cell
- contexts
- research
- method types
- foundation_model
- entity level
- family
- reported name
- scBERT
- source locator
- Main text paragraph 2; reference 4; Methods 'Software versions and parameters'
- missing metadata
- version: reason: inapplicable; note: Family record; the commit is on the configuration
Related records
- configuration of: scBERT (Ahlmann-Eltze et al. 2025)