Author

Florian W. R. Vondran

Medizinische Hochschule HannoverORCID 0000-0001-8355-5017Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Florian W. R. Vondran1 paper

Biology Disciplines

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Bioinformatics· 1 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Assay:imaging· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Ahmed GhallabiD· 1 shared Ana Jordan-PaiziD· 1 shared Andrew J. HightoniD· 1 shared Angelique HölzemeriD· 1 shared Annika NiehrsiD· 1 shared Christoph SchrammiD· 1 shared Colm J. O’RourkeiD· 1 shared Daniel HeiseiD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperCancer Biology

Ahmed GhallabORCID

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2 papers

Recent·Most cited

Cancer Biologynpj Precision OncologyPeer-reviewedJan 28, 2026

Multimodal single-cell profiling reveals cancer crosstalk between macrophages and stromal cells in poor prognostic cholangiocarcinoma patients.

Lara Rosaline Heij, Sikander Hayat, Konrad Reichel…·Ulf P. Neumann

This study uses multimodal single-cell profiling to identify immune cell crosstalk mechanisms in poor prognostic cholangiocarcinoma, revealing key ligand pairs and pathways contributing to immune exhaustion.

3 citationstop 2%

humanspatial transcriptomics

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BioinformaticsbioRxivPreprintSep 6, 2022

GOAT: Deep learning-enhanced Generalized Organoid Annotation Tool

Jan P. Bremer, Martin E. Baumdick, Marius S. Knorr…·Madeleine J. Bunders

GOAT is a deep learning tool for annotating organoids from microscopy images, showing high performance across diverse organoid systems.

1 citation

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