Top Tweets for #CellOT
โThe paper is a step forward in terms of understanding the heterogeneous response of different cell states to environmental perturbations.โ
๐ฅ #SIBRemarkableOutputs 2023 ๐
๐ Find out more about this and the other outputs: https://t.co/lzhpZNHeWx
#CellOT #MachineLearning
Super excited that our work #CellOT was selected among SIB's Remarkable Outputs 2023๐: Curious about how we can predict single-cell responses to perturbations? Take a look at our @NatureMethods paper (https://t.co/6uRLQPckiN) and the Research Briefing (https://t.co/K5QwdNUqem)!
Our latest newsletter is out!
Discover SIBโs 2023 Remarkable Outputs highlighting seven outstanding contributions from our members to the #bioinformatics field. Find out how #viruses ๐ฆ can communicate with bacteria and the latest #insilicotalks https://t.co/1tx1Mm9QCq

#CellOT: Neural optimal transport for predicting perturbation response of single cells! Fantastic collaboration with @_bunnech @stefangstark @GabriGut and others from @gxr and @lucaspelkmans groups at @ETH_AI_Center @ETH_en @UZH @USZ
Using #MachineLearning, experts from ETH Zurich, @UZH and @USZ have jointly developed a new approach that can predict how individual #Cells will react to #SpecificTreatments, offering hope for more #AccurateDiagnostics and therapeutics. ๐งซ
Learn more: ๐ https://t.co/KjK5r2lX6o
#CondOT (@neuripsconf 2022) generalizes #CellOT and allows conditioning the inferred responses on a context, e.g., patient meta-information. This is crucial when moving to prediction tasks on patient cohorts ๐ฅ!
https://t.co/x7r8xgAf0k

The first method, #CellOT (@naturemethods) uses optimal transport to accurately predict single-cell responses to various drugs or developmental signals. We learn a neural #Monge map that transforms the unperturbed cell population into its perturbed state.
https://t.co/6uRLQPckiN
Stefan Stark @stefangstark on #CellOT for out of sample tumor profiling & modeling cancer therapy responses #biodata22
๐ https://t.co/Rn1kvGRvSE
๐งฐ https://t.co/FiSISBFYxb

Next up is @stefangstark on modeling #SingleCell responses to perturbations using optimal transport! #biodata22

By enforcing this strong regularization and without the dependency on a meaningful latent space, #CellOT outperforms existing state-of-the-art methods and accurately matches cellular features after perturbation.

Check out our work on predicting #singlecell perturbation responses using neural optimal transport (#CellOT), which we presented at the #OTML Workshop at @NeurIPS 2021.
Paper: https://t.co/j4P3RO1gr7

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