Author

Michael W. Deininger

German Cancer Research CenterORCID 0000-0002-2987-1331Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Cancer Biology· 1 Pathology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Organism:human· 2 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Organism:mouse· 1

Frequent Co-Authors

Brandon HadlandiD· 1 shared Danielle C. KirkeyiD· 1 shared Derek Stirewalt· 1 shared Doan BuiiD· 1 shared Dominik Faerber· 1 shared Eric PadroniD· 1 shared Florian BuettneriD· 1 shared Helong ZhaoiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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1 shared paperPathology

Brandon HadlandORCID

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2 papers

Recent·Most cited

Cancer BiologyHaematologicaPeer-reviewedSep 3, 2026

Single-cell RNA editing defines clinically relevant cellular states in chronic myelomonocytic leukemia

Nisansala Wickramasinghe, Doan Bui, Surendra Neupane…·Tongjun Gu

This study identifies RNA editing-defined cellular states in CMML that correlate with clinical outcomes and therapeutic response.

DOI 10.3324/haematol.2026.301007

PathologybioRxivPreprintOct 20, 2025

Cross-Species Morphology Learning Enables Nucleic Acid-Independent Detection of Live Mutant Blood Cells

Sarmad Ahmad Khan, Dominik Faerber, Danielle C. Kirkey…·Helong Zhao

This paper introduces a computer vision platform that detects live mutant blood cells with specific mutations using morphology recognition, without requiring nucleic acid sequencing.

DOI 10.1101/2025.10.20.682949