Modeling Cell-Cycle-Aware Single-Cell Drug Perturbation Responses
Single-cell drug perturbation models should capture transcriptional response magnitude and whether a treatment changes the proliferative state of the cell. This is difficult because cell-cycle variation is often treated as a nuisance factor, and benchmark processing rarely makes drug-induced phase changes a primary prediction target. We introduce scCycleMol, a cell-cycle-aware perturbation prediction framework built on a curated 24-hour SciPlex3 benchmark with standardized molecule identities, dose and cell-line metadata, modeled genes, and expression-derived cell-cycle supervision. scCycleMol derives cell-cycle supervision from the treated state and applies it to predicted treated expres...
| Authors | Dingping Zhao, Jie Lin, Feng Xu et al. |
|---|---|
| Primary category | q-bio.QM |
| Published | 29 June 2026 |
| Last updated at source | 3 July 2026 |
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