Author

Noëlle Dommann

University of BernORCID 0000-0003-0475-0899Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Cancer Biology· 1 Developmental Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Research Focus:differential expression· 2 Assay:scRNA-seq· 2 Approach:Bayesian inference· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Organism:human· 1 Organism:mouse· 1

Frequent Co-Authors

Adrian KeoghiD· 2 shared Daniel CandinasiD· 2 shared Daniel Sánchez‐TaltavulliD· 2 shared Deborah StrokaiD· 2 shared Guido BeldiiD· 2 shared Nicolas MéliniD· 2 shared Ali ErtürkiD· 1 shared Amber K. L. WezenaariD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersDevelopmental Biology

Adrian KeoghORCID

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Author profile →

3 papers

Recent·Most cited

De novo H3.3K27M-altered Diffuse Midline Glioma in human brainstem organoids to dissect GD2 CAR T cell function

Nils Bessler, Amber K. L. Wezenaar, Hendrikus CR Ariese, Celina Honhoff, Noëlle Dommann, Ellen J. Wehrens, Cristian Ruiz-Moreno, Thijs J M van den Broek, Raphaël V U Collot, Daan J. Kloosterman, Farid Keramati, Mieke M Roosen, Sam de Blank, Esmée J. van Vliet, Mario Barrera Román, , Anne C. Rios

This paper develops a human brainstem organoid model of H3.3K27M-altered DMG to study GD2 CAR T cell function and identify therapeutic targets.

Nature Cancer · Jan 5, 2026Peer-reviewedCancer Biology

Single cell chronoatlas of regenerating mouse livers reveals early Kupffer cell proliferation

Daniel Sánchez‐Taltavull, Tess Melinda Brodie, Joël Zindel, Noëlle Dommann, Bas G. J. Surewaard, Adrian Keogh, Nicolas Mélin, Isabel Büchi, Riccardo Tombolini, Paul Kubes, Daniel Candinas, Guido Beldi, Deborah Stroka

This study creates a single-cell time atlas of mouse liver regeneration after partial hepatectomy, revealing Kupffer cells as the first proliferating cell type.

bioRxiv · Jun 9, 2021 · PreprintDevelopmental Biology

Bayesian Correlation is a robust similarity measure for single cell RNA-seq data

Daniel Sánchez‐Taltavull, Theodore J. Perkins, Noëlle Dommann, Nicolas Mélin, Adrian Keogh, Daniel Candinas, Deborah Stroka, Guido Beldi

The paper introduces Bayesian correlation as a robust similarity measure for scRNA-seq data, showing it outperforms Pearson correlation in reproducibility and biological relevance.

NAR Genomics and Bioinformatics · Jan 24, 2020Peer-reviewedBioinformatics