Happy to share CellAnnotator, a lightweight Python package to query OpenAI models for initial cell type annotations: github.com/quadbio/cell... Inspired by ideas in www.nature.com/articles/s41... and github.com/VPetukhov/GP..., implemented as an scVerse ecosystem package with docs and tutorials.

From cell lines to full embryos, drug treatments to genetic perturbations, neuron engineering to virtual organoid screens — odds are there’s something in it for you! Built on flow matching, CellFlow can help guide your next phenotypic screen: biorxiv.org/content/10.1101/2025.04.11.648220v1

Our paper benchmarking feature selection for scRNA-seq integration and reference usage is out now www.nature.com/articles/s41...! Keep reading for more about how we did the study and what we found out 🧵 👇 1/16

🚨🧠 New paper alert: Stress alters neuronal balance in the developing brain 🧠🚨 Our latest study in @science.orgAdvances explores how glucocorticoid exposure—a key environmental risk factor—shapes early human brain development using #organoids. @mpi-psychiatry.bsky.social @drcricru.bsky.social 🧵👇

Insightful study by L. Dony @anthikrontira.bsky.social @drcricru.bsky.social @binderlabmpip.bsky.social @silvianeuro.bsky.social @fabiantheis.bsky.social on the effects of chronic exposure to glucocorticoids for neurodevelopment. Organoid model reveals amplification of inhibitory neuron cell fate 🧪

When applying machine learning to human health data, it is not enough to just improve a metric by another percent. We have to go deeper. In our perspective in Nature Cell Biology, we discuss caveats and biases of human single-cell data analysis: nature.com/articles/s41... 🧵 1/10

Good to see moscot-tools.org published in @nature.com ! We made existing Optimal Transport (OT) applications in single-cell genomics scalable and multimodal, added a novel spatiotemporal trajectory inference method and found exciting new biology in the pancreas! tinyurl.com/33zuwsep

If diving into scientific papers isn’t on your pre-Christmas to-do list, @spiegel.de has you covered! 📰 They featured our Neural Organoid Atlas in a piece on the Human Cell Atlas and related advancements in machine learning. 🤖🧬 It’s a great overview of this exciting field and the work behind it.

Super excited to share our Human Neural Organoid Atlas, now out in Nature! Led by @zhisonghe.bsky.social @josch1.bsky.social, and myself, this resource was created from 36 scRNA-seq datasets—totalling over 1.7 million cells! 🔬✨
 www.nature.com/articles/s41...
 Find out how it can serve you ⏬
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