single-cell/cpa

Overview

The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell level. CPA performs OOD predictions of unseen combinations of drugs, learns interpretable embeddings, estimates dose-response curves, and provides uncertainty estimates.

Test this model

Not servable. No inference endpoint is declared for this model, so there is nothing to call — no button here and no API route for it. What makes a model servable

Papers

• Predicting cellular responses to complex perturbations in high-throughput screens.Reference
  Molecular Systems Biology, 2023DOI: 10.15252/msb.202211517 ↗