Author

Théo Uscidda

Helmholtz Munich

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Assay:scRNA-seq· 1 Research Focus:trajectory inference· 1

Frequent Co-Authors

Alejandro Tejada-LapuertaiD· 1 shared Alessandro PalmaiD· 1 shared Artur SzałataiD· 1 shared Aviv RegeviD· 1 shared Barbara TreutleiniD· 1 shared Daniil M. BobrovskiyiD· 1 shared Dominik KleiniD· 1 shared Fabian Joachim TheisiD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperBioinformatics

Alejandro Tejada-LapuertaORCID

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1 paper

Recent·Most cited

CellFlow enables generative single-cell phenotype modeling with flow matching

Dominik Klein, Jonas Simon Fleck, Daniil M. Bobrovskiy, Lea Zimmermann, Sören Becker, Alessandro Palma, Leander Dony, Alejandro Tejada-Lapuerta, Guillaume Huguet, Hsiu‐Chuan Lin, Nadezhda V. Azbukina, Fátima Sanchís-Calleja, Théo Uscidda, Artur Szałata, Manuel Gander, , Fabian Joachim Theis

CellFlow predicts single-cell phenotypes from complex perturbations using flow matching, demonstrating accuracy in cytokine stimulation, drug treatments, and developmental modeling.

bioRxiv · Apr 11, 2025 · PreprintBioinformatics