OCOO-T is a flow-matching Transformer model that directly denoises continuous gene expression profiles to predict transcriptional responses to perturbations and reports state-of-the-art results on Tahoe100M, Replogle, and PBMC benchmarks.
Exploring genetic interaction manifolds constructed from rich single-cell phenotypes
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Task-aligned supervised geometric stability predicts linear steerability with high accuracy while unsupervised stability detects representational drift earlier and with lower false alarms than CKA or Procrustes.
Geometric stability, defined as the directional coherence of cellular responses to perturbation, provides a framework for assessing whether resulting cellular states are stable beyond conventional metrics of intervention success.
citing papers explorer
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OCOO-T : A Simple and Scalable Virtual Cell Model for Transcriptional Perturbation Response Prediction
OCOO-T is a flow-matching Transformer model that directly denoises continuous gene expression profiles to predict transcriptional responses to perturbations and reports state-of-the-art results on Tahoe100M, Replogle, and PBMC benchmarks.
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The Geometric Canary: Predicting Steerability and Detecting Drift via Representational Stability
Task-aligned supervised geometric stability predicts linear steerability with high accuracy while unsupervised stability detects representational drift earlier and with lower false alarms than CKA or Procrustes.
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From Syntax to Semantics: Geometric Stability as the Missing Axis of Perturbation Biology
Geometric stability, defined as the directional coherence of cellular responses to perturbation, provides a framework for assessing whether resulting cellular states are stable beyond conventional metrics of intervention success.
- Geometric coherence of single-cell CRISPR perturbations reveals regulatory architecture and predicts cellular stress