716-stVCR: Spatiotemporal Single-Cell Dynamics

Paper Talk · Mar 30, 2026 · 24m

The paper introduces stVCR, a generative deep-learning framework designed to reconstruct the continuous spatiotemporal dynamics of single cells from discrete snapshots. Because traditional spatial transcriptomics involves destructive sequencing, it typically produces unpaired "pictures" of biological processes rather than a continuous "video." To bridge this gap, stVCR utilizes dynamic optimal transport and rigid-body transformation to align data from different time points into a single coordinate system. This allows researchers to track cell differentiation, migration, and proliferation…