Author

Beatrice Beck‐Schimmer

University of ZurichORCID 0000-0002-0648-6115Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:scRNA-seq· 2 Approach:statistical model· 2 Research Focus:batch correction / integration· 1 Research Focus:cell type annotation· 1 Assay:CITE-seq· 1

Frequent Co-Authors

Abdullah KahramaniD· 2 shared Alva Rani JamesiD· 2 shared André Fedier· 2 shared André KahlesiD· 2 shared Andrea Jacobs· 2 shared Anja IrmischiD· 2 shared Anne BertoliniiD· 2 shared Berend SnijderiD· 2 shared

Activity by Year

2020-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Abdullah KahramanORCID

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2 papers

Recent·Most cited

BioinformaticsNAR Genomics and BioinformaticsPeer-reviewedJun 1, 2022

scROSHI - robust supervised hierarchical identification of single cells

Michael Prummer, Anne Bertolini, Lars Bosshard…·Berend Snijder

scROSHI identifies cell types without training data by using pre-existing gene sets and hierarchical relationships, outperforming methods in low-data and high-diversity scenarios.

11 citations

humanscRNA-seq

𝕏 PostBluesky

BioinformaticsBioinformaticsPeer-reviewedSep 14, 2020

SCIM: Universal Single-Cell Matching with Unpaired Feature Sets

Stefan G. Stark, Joanna Ficek, Francesco Locatello…·Vipin T. Sreedharan

SCIM matches single-cell measurements across technologies by learning a technology-invariant latent space and applying bipartite matching, achieving high accuracy in real-world datasets.

56 citations

humanscRNA-seq

𝕏 PostBluesky