Author

Oliver E. Hunewald

Luxembourg Institute of HealthORCID 0000-0001-5402-5084Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Organism:mouse· 2 Research Focus:cell type annotation· 1 Assay:CITE-seq· 1 Research Focus:clustering· 1 Organism:human· 1 Approach:large language model· 1 Assay:multiome· 1 Approach:statistical model· 1

Frequent Co-Authors

Annette KuehniD· 1 shared Christophe TrefoisiD· 1 shared Erica T. GrantiD· 1 shared Jiřı́ VondrášekiD· 1 shared Laurent HeirendtiD· 1 shared Mahesh S. DesaiiD· 1 shared Markus W. OllertiD· 1 shared Miroslav KratochvíliD· 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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1 shared paperBioinformatics

Annette KuehnORCID

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintOct 24, 2026

Language models annotate mass cytometry clusters within the range where human experts disagree

Oliver E. Hunewald, Erica T. Grant, Theresa-Maria Boehm…·Petr V. Nazarov

This paper uses large language models to annotate mass cytometry clusters, achieving high concordance with expert annotations and outperforming baselines.

DOI 10.64898/2026.10.20.760379

humanmouse

𝕏 PostBluesky

BioinformaticsGigaSciencePeer-reviewedNov 1, 2020

GigaSOM.jl: High-perfomance clustering and visualization of huge cytometry datasets

Miroslav Kratochvíl, Oliver E. Hunewald, Laurent Heirendt…·Markus W. Ollert

GigaSOM.jl provides a scalable solution for clustering and visualizing large cytometry datasets, achieving high performance with distributed computing.

13 citations

mouseCITE-seq

𝕏 PostBluesky