Author

Patrick Sven Plum

University of CologneORCID 0000-0002-8165-4553Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Research Focus:differential expression· 3 Organism:human· 3 Research Focus:cell type annotation· 2 Approach:deep learning· 2 Assay:scRNA-seq· 2 Approach:statistical model· 2 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Alexander QuaasiD· 3 shared Christiane J. BrunsiD· 3 shared Axel M. HillmeriD· 2 shared Marek Franitza· 2 shared Marten C Wenzel· 2 shared Sascha HoppeiD· 2 shared Abdossamad Hamoudi· 1 shared Andreas BeyeriD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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3 shared papersCancer Biology

Alexander QuaasORCID

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3 papers

Recent·Most cited

Gene expression adaptation of metastases to their host tissue

Luise Nagel, Marten C Wenzel, Sascha Hoppe, Mohammad Karimpour, Patrick Sven Plum, Abdossamad Hamoudi, Israt Jahan, S Schmitt, Marek Franitza, Roger Wahba, Marc Bludau, Christiane J. Bruns, Alexander Quaas, Andreas Beyer, Axel M. Hillmer

This study identifies gene expression adaptations of metastases to host tissue using single-cell RNA-sequencing and a novel computational approach, revealing liver-specific expression signatures in colorectal cancer metastases.

iScience · Jul 21, 2026Peer-reviewedCancer Biology

Single cell analysis of Barrett's esophagus and carcinoma reveals cell types conferring risk via genetic predisposition

Marten C Wenzel, Pouria Dasmeh, Patrick Sven Plum, Ann-Sophie Giel, Sascha Hoppe, Marek Franitza, Christoph Jonas, René Thieme, Yue Zhao, Dominik Heider, Claire Palles, Rebecca Claire Fitzgerald, Christiane J. Bruns, Reinhard Buettner, Alexander Quaas, , Axel M. Hillmer

The paper uses single cell RNA-sequencing and genome-wide association study data to identify cell types and processes involved in Barrett's esophagus and esophageal adenocarcinoma risk.

Cell Genomics · Sep 8, 2025Peer-reviewedCancer Biology

Predicting the HER2 status in esophageal cancer from tissue microarrays using convolutional neural networks

Juan I. Pisula, Rabi Raj Datta, Leandra Börner Valdez, Jan-Robert Avemarg, Jin‐On Jung, Patrick Sven Plum, Heike Löser, Philipp Lohneis, Monique Meuschke, Daniel Pinto dos Santos, Florian Gebauer, Alexander Quaas, Christiane J. Bruns, Axel Karl Walch, Kai Lawonn, , Katarzyna Bożek

This paper develops a CNN-based method to predict HER2 status in esophageal cancer tissue microarrays with high accuracy, outperforming manual assessment and reducing the need for costly follow-up tests.

bioRxiv · May 13, 2022 · PreprintBioinformatics