YC

We built the first world model of the cell — and, we believe, the first to unify all four of its axes into one shared state. Expression, morphology, spatial context, and time have always been measured in separate experiments, on separate platforms, in separate distributions; no one had made them a single thing. We forced all four into one latent state you can read, roll forward in time, intervene on, and decode back into an image. This is what today's virtual-cell field lacks: STATE, TranscriptFormer, scGPT, GeneFlow, and Spatia are essentially single-modality transcriptomics predicting perturbation → expression — none unifies four axes, and none is a true world model. And we proved each axis is real, not an artifact, with a negative (shuffle) control on every one: expression reconstruction R² = 0.57; real spatial neighbors beat shuffled at z = −181 (p < 0.001); expression recovers morphology at r ≈ 0.66–0.68. We even report our failure honestly — the sharpest generated images were hallucinations, so we kept the coarse-but-correct one. Once four axes share one state, it becomes a universal adapter: reconstruct a modality a dataset never measured, transfer across platforms, run in-silico perturbations, and scale from 200k cells to 100M-cell atlases.