Target-gene dropout rate baseline (Kendiukhov 2026)
Dropout rate of each candidate target gene.
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Evaluations and results
1 evaluation · 1 result. Different protocols are not a single leaderboard.
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| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: Target-gene dropout rate baseline (Kendiukhov 2026) | Protocol: Perturbation-first AUROC, RPE1 CRISPRi (Kendiukhov 2026) Dataset subset: Replogle genome-scale CRISPRi, RPE1, 1,167 perturbations, confound battery (Kendiukhov 2026) | 0.797 AUROC (per-perturbation AUROC for DE targets, summarised over perturbations; RPE1 CRISPRi) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourcegfm-guides-20261014-kendiukhov2026-protocol-pf-rpe1-crispri Aggregation: Not reported Systematic evaluation of single-cell foundation model interpretability: attention-derived edge scores add no incremental value over gene-level features for perturbation-target prediction (Kendiukhov 2026, BMC Genomics 27:634) · Page 10, 'Cross-cell-type generalisation of confound pattern', item (i): 'variance AUROC = 0.866, mean expression = 0.851, dropout = 0.797 vs. attention = 0.747 and correlation = 0.658' |
Source checking is not independent reproduction. Release 2026-11-02-a7f03c9e55a5.
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Evidence
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Sources and history
Release 2026-11-02-a7f03c9e55a5 · Record review: source checked
1 source record and release history
- Systematic evaluation of single-cell foundation model interpretability: attention-derived edge scores add no incremental value over gene-level features for perturbation-target prediction (Kendiukhov 2026, BMC Genomics 27:634) · Original source · Version of record, BMC Genomics 27:634, published 2026-07-22 (received 2026-03-10, accepted 2026-05-14)
Technical metadata and extraction receipts
Stable ID: gfm-guides-20261014-kendiukhov2026-config-gene-dropout-rate
- areas
- single-cell; biological-networks
- contexts
- research
- method types
- conventional_pipeline
- reported name
- dropout
- foundation model eligible
- false
- representation
- Dropout rate of each candidate target gene.
- source locator
- Page 13 'Models and data', 'Attention extraction and edge score computation', 'Model coverage by analysis family'
- training setting
- Computed from each dataset's control cells
- access reuse
- Analysis code github.com/Biodyn-AI/biomechinterp-framework and Zenodo 10.5281/zenodo.18701417; not pinned to a commit in the article
- missing metadata
- version: reason: inapplicable; note: Defined in the article