scCycleMol adds a learnable circular cell-cycle head with closed-loop supervision from predicted treated expression, yielding higher r-squared on SciPlex3 gene predictions and improved phase accuracy versus ChemCPA baselines.
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Chem2Gen-Bench is a new benchmark and evaluation framework for measuring alignment between chemical and genetic perturbation responses in matched cell-target contexts using retrieval, similarity, and embedding comparisons.
A new harmonized multi-dataset resource of small molecule perturbation transcriptomics is introduced, revealing weak cross-dataset logFC agreement but improved compound embedding performance in held-out evaluations.
PRiMeFlow applies flow matching in gene expression space with a U-Net velocity field and pretraining-finetuning to model perturbation-induced heterogeneity, showing strong benchmark performance on PerturBench and the ARC Virtual Cell Challenge.
citing papers explorer
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Modeling Cell-Cycle-Aware Single-Cell Drug Perturbation Responses
scCycleMol adds a learnable circular cell-cycle head with closed-loop supervision from predicted treated expression, yielding higher r-squared on SciPlex3 gene predictions and improved phase accuracy versus ChemCPA baselines.
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Chem2Gen-Bench: Benchmarking Chemical-to-Genetic Translation in Perturbation Response Space
Chem2Gen-Bench is a new benchmark and evaluation framework for measuring alignment between chemical and genetic perturbation responses in matched cell-target contexts using retrieval, similarity, and embedding comparisons.
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Chem-PerturBridge: a harmonized compendium of small molecule perturbation transcriptomic effects
A new harmonized multi-dataset resource of small molecule perturbation transcriptomics is introduced, revealing weak cross-dataset logFC agreement but improved compound embedding performance in held-out evaluations.
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PRiMeFlow: Capturing Complex Expression Heterogeneity in Perturbation Response Modelling
PRiMeFlow applies flow matching in gene expression space with a U-Net velocity field and pretraining-finetuning to model perturbation-induced heterogeneity, showing strong benchmark performance on PerturBench and the ARC Virtual Cell Challenge.