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dominik1klein.bsky.social @dominik1klein.bsky.social · Apr 25

Also check out the cell fate engineering applications:
bsky.app/profile/josc...

jonas @josch1.bsky.social · Apr 24

CellFlow is particularly good at modeling complex and heterogenous cell distributions. When applied to an iNeuron morphogen screen from @hsiuchuanlin.bsky.social & @jasperjanssens.bsky.social, it correctly predicts emergent cell populations arising from combinatorial morphogen treatment.

dominik1klein.bsky.social @dominik1klein.bsky.social · Apr 23

@chatgtp.bsky.social, Manuel, A. Regev, B. Treutlein, @graycamplab.bsky.social, @fabiantheis.bsky.social

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dominik1klein.bsky.social @dominik1klein.bsky.social · Apr 23

CellFlow was a highly collaborative team effort. Thanks to the great co-lead @josch1.bsky.social , and the fantastic team Daniil, Lea, Soeren, Alessandro, @le-and-er.bsky.social, Alejandro, @guillaumehu.bsky.social, @hsiuchuanlin.bsky.social, @nazbukina.bsky.social, Fatima, Theo,

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dominik1klein.bsky.social @dominik1klein.bsky.social · Apr 23

Check out the paper for more applications, including cell fate engineering and organoid protocol optimisation!

Head to cellflow.readthedocs.io for tutorials, and get in touch—Plenty of exciting directions to explore!

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dominik1klein.bsky.social @dominik1klein.bsky.social · Apr 23

We found CellFlow to consistently perform competitively across various benchmarks, including drug and genetic perturbation screens - while being able to address complex experimental setups other methods are not able to address.

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dominik1klein.bsky.social @dominik1klein.bsky.social · Apr 23

We let CellFlow learn the perturbed development of entire embryos, allowing to model the continuous trajectories of single cells under different genetic perturbations.

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dominik1klein.bsky.social @dominik1klein.bsky.social · Apr 23

We predicted donor-specific cytokine responses on 10 million cells! We found CellFlow to exhibit scaling laws in the number of seen conditions and gained interpretable insights into model training.

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dominik1klein.bsky.social @dominik1klein.bsky.social · Apr 23

CellFlow builds on flow matching, optimal transport & attention mechanisms to learn an embedding of complex experimental conditions. This guides the flow from control to perturbed cells, generating realistic states while minimizing displacement costs.

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dominik1klein.bsky.social @dominik1klein.bsky.social · Apr 23

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

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Reposted

jonas @josch1.bsky.social · Apr 18

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

CellFlow enables generative single-cell phenotype modeling with flow matching

High-content phenotypic screens provide a powerful strategy for studying biological systems, but the scale of possible perturbations and cell states makes exhaustive experiments unfeasible. Computatio...

www.biorxiv.org

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Reposted

Nadezhda Azbukina @nazbukina.bsky.social · Mar 24

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!

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Reposted

Stephen Turner @stephenturner.us · Jan 23

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

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Reposted

Nature @nature.com · Jan 23

Nature research paper: Mapping cells through time and space with moscot

https://go.nature.com/40pqpvw

Mapping cells through time and space with moscot - Nature

Moscot is an optimal transport approach that overcomes current limitations of similar methods to enable multimodal, scalable and consistent single-cell analyses of datasets across spatial and temporal dimensions.

go.nature.com

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dominik1klein.bsky.social @dominik1klein.bsky.social · Jan 23

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)

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dominik1klein.bsky.social @dominik1klein.bsky.social · Jan 23

@AimeeBastidas, @pacotael, @MartaTarquis, @ShreyParikh07, Ilan Gold, @heikolickert.bsky.social , @mostafabakhti.bsky.social @marcocuturi.bsky.social , @fabiantheis.bsky.social

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dominik1klein.bsky.social @dominik1klein.bsky.social · Jan 23

This was a highly collaborative project, thanks to everyone involved, in particular to the co-leads @giopll.bsky.social , @mariuslange.bsky.social , Michal Klein, Zoe Piran, as well as Manuel Gander, @Laetitia_Ppx, Michael Sterr, @lamasa LamaSaber95, @Diana61204366,

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dominik1klein.bsky.social @dominik1klein.bsky.social · Jan 23

moscot integrates straightforwardly with the @scverse.bsky.social ecosystem. Check out our tutorials and examples at moscot-tools.org to analyze your single-cell data, we encourage the community to contribute to moscot with novel OT applications!

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dominik1klein.bsky.social @dominik1klein.bsky.social · Jan 23

moscot’s ability to study gene regulation allowed us to hypothesise Neurod2 to be an activator of epsilon cell formation. We indeed observed a reduction in ghrelin (hormone produced by eps. cells) in NEUROD2 knockout iPSCs

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dominik1klein.bsky.social @dominik1klein.bsky.social · Jan 23

We generated a new dataset of the developing mouse pancreas across three time points with paired measurements of gene expression and ATAC data. Enrichment of Ngn3 high cells allows us to disentangle the poorly understood formation of delta and epsilon cells.

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dominik1klein.bsky.social @dominik1klein.bsky.social · Jan 23

We develop a new method for the analysis of spatiotemporal datasets. We show how incorporating the spatial information improves the recovery of cell trajectories and demonstrate its use in a spatially resolved mouse embryogenesis dataset.

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dominik1klein.bsky.social @dominik1klein.bsky.social · Jan 23

Moscot aligns large-scale spatial transcriptomics slides from different individuals to obtain a statistically more profound representation of the mouse brain.

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dominik1klein.bsky.social @dominik1klein.bsky.social · Jan 23

We map CITE-seq data of the mouse liver to a spatial reference slide incorporating information from gene expression, protein, and spatial measurements, facilitating liver zonation.

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dominik1klein.bsky.social @dominik1klein.bsky.social · Jan 23

Incorporating recent advances in OT, we make moscot scalable to atlas-scale datasets (see ott-jax.readthedocs.io/en/latest/, @marcocuturi.bsky.social). This allows to to recover trajectories in an atlas of mouse embryogenesis comprising 1.7 million cells.

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dominik1klein.bsky.social @dominik1klein.bsky.social · Jan 23

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

Mapping cells through time and space with moscot - Nature

Moscot is an optimal transport approach that overcomes current limitations of similar methods to enable multimodal, scalable and consistent single-cell analyses of datasets across spatial and temporal...

tinyurl.com

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Reposted

Fabian Theis @fabiantheis.bsky.social · Jan 22

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...

Mapping cells through time and space with moscot - Nature

Moscot is an optimal transport approach that overcomes current limitations of similar methods to enable multimodal, scalable and consistent single-cell analyses of datasets across spatial and temporal...

www.nature.com

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