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

Yay, we built a thing! With @dominik1klein.bsky.social Daniil, Aviv Regev, Barbara Treutlein @graycamplab.bsky.social @fabiantheis.bsky.social we use flow matching to enable generalised sc phenotype modeling. From cytokine screens to fate programming and organoid engineering tinyurl.com/3xhju7db

Excited to share our latest preprint, presenting a multi-omic human neural organoid cell atlas of the posterior brain! 🧠🔬 doi.org/10.1101/2025... Great work with @hsiuchuanlin.bsky.social @zhisonghe.bsky.social @graycamplab.bsky.social and Barbara Treutlein!

Mapping cells through time and space with moscot https://www.nature.com/articles/s41586-024-08453-2 🧬🖥️🧪 https://github.com/theislab/moscot

Nature research paper: Mapping cells through time and space with moscot https://go.nature.com/40pqpvw

Missing the deep learning part? go check out the follow up work @neuripsconf.bsky.social (tinyurl.com/yvf72kzf) and @iclr-conf.bsky.social (tinyurl.com/4vh8vuzk)

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

Excited to see Moscot (moscot-tools.org) published in @Nature! We scaled Optimal Transport (OT) in single-cell genomics & added multimodality together with spatiotemporal trajectory inference, finding exciting new biology in the pancreas! 🚀 Read at www.nature.com/articles/s41...

Exciting new tool to make the most out of multimodal single-cell data from our friends and long-term collaborators of the @fabian_theis lab - check it out, it works beautifully and really makes sense out of your complex data! 👇👍😉

Today is a great day for optimal transport 🎉! Lots of gratitude 🙏 for all folks who contributed to ott-jax.readthedocs.io and pushed for the MOSCOT (now @ nature!) paper, from visionaries @dominik1klein.bsky.social, G. Palla, Z. Piran to the magician, Michal Klein! ❤️ www.nature.com/articles/s41...

1/2 🚀 Discrete Optimal Transport (OT) has proved useful in a wide variety of tasks in single-cell genomics, see e.g. moscot-tools.org. Can we combine this powerful concept this with novel generative models? 🤔 🌟 Enter GENOT: Generative Entropic Neural OT.