Gene-level logistic regression (mean expression, variance, dropout rate)
Logistic regression on gene-level features of the candidate target gene, trained under 5-fold GroupKFold by perturbation.
Results are recorded on linked configurations and versions of this method. Their settings and evaluations are kept separate below.
Results on linked records
This method has no results of its own in this release. 3 linked records have results. They are not assigned to the underlying method: each record keeps its own settings and evaluations, and its scores are on its own page.
- Gene-level logistic regression (Kendiukhov 2026) Configuration · configuration of this method · 2 evaluations · 2 results
- Gene-level logistic regression plus attention edge (Kendiukhov 2026) Configuration · configuration of this method · 3 evaluations · 3 results
- Gene-level logistic regression plus correlation edge (Kendiukhov 2026) Configuration · configuration of this method · 2 evaluations · 2 results
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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-method-gene-level-logistic-regression
- areas
- single-cell; biological-networks
- contexts
- research
- method types
- supervised_machine_learning
- reported name
- Gene-level features
- entity level
- method
- source locator
- Page 4 'Evaluation framework'; page 13 'Model coverage by analysis family'; page 14 'Confound decomposition'
- missing metadata
- version: reason: inapplicable; note: Simple statistic or model defined in the article
Related records
- configuration of: Gene-level logistic regression (Kendiukhov 2026)
- configuration of: Gene-level logistic regression plus attention edge (Kendiukhov 2026)
- configuration of: Gene-level logistic regression plus correlation edge (Kendiukhov 2026)