Stable-Shift: Biologically Structured Prediction of Transcriptional Responses to Unseen Gene Perturbations
Predicting transcriptional responses to genetic perturbations could reduce the experimental burden of functional genomics, but extrapolation to genes that were never perturbed during training remains difficult. We present Stable-Shift, a structured method for estimating unseen-gene responses. Stable-Shift aggregates single-cell measurements into perturbation-level expression shifts, fits a low-rank response basis using training perturbations only, and predicts an unseen gene's coordinates in that basis from biological context. The context combines STRING interactions, network structure, control-cell expression statistics, and Gene Ontology annotations; the evaluated implementation uses gr...
| Authors | Sajib Acharjee Dip, Liqing Zhang |
|---|---|
| Primary category | q-bio.GN |
| Published | 22 June 2026 |
| Last updated at source | 22 June 2026 |
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