Preprint: cell transcriptional state can't predict fate, but lineage context can
stats_stephen · x · 2026-11-07
A new preprint led by goklg, njwfish and WilliamNColgan (with Philippe Rigollet, statsstephen, Marinka Zitnik, lukekoblan and others) models mouse embryos as trees via generative modeling rather than single-cell trajectories.
Key finding: a cell's transcriptional state is generally not sufficient to predict its past or future, but conditioning on lineage context (sisters, cousins, etc.) substantially improves prediction.
Related event: MIT team models mouse embryonic development with generative modeling(2 posts)→
More from Research
- Amortized Reasoning Index: a 0.4B retriever continuously RL-trained by a big model matches 8B — lateinteraction · 2026-11-07
- GLASS preprint teaser: graph-led LLM-assisted scoring of open-ended responses without human coding — GolinoHudson · 2026-11-07
- LLMs can read and patch weights, but 20 fine-tuning steps erase the edits — kevinpl07 · 2026-11-07
- FlexiTac-Gen launches: AI-agent-assisted tool to design custom tactile sensors, accepted to CoRL 2026 — Haoyu_Xiong_ · 2026-11-07
- PolicyIK: NYU trains RL for inverse kinematics on a real arm, hitting 0.5mm median error — Lianhuiq · 2026-11-07
- Weight-space programming vs LoRA on 4 bugs: precise one-neuron patches that don't persist — kevinpl07 · 2026-11-07