Author

M. Halder

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cancer Biology· 1 Cell Biology· 1 Pathology· 1

Signature Assays, Organisms & Methods

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

Frequent Co-Authors

R. Kramann· 2 shared A. Heim· 1 shared A.-K. Thebille· 1 shared C. F. Krebs· 1 shared C. Kleinhempel· 1 shared C. Kuppe· 1 shared C. Rourke· 1 shared D. Cladiere· 1 shared

Activity by Year

2020-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 15 mutual co-author links

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2 shared papersCancer Biology

R. Kramann

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

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

L. R. Heij, S. Hayat, K. Reichel, S. Maryam, C. Rourke, X. Tan, M. van den Braber, J. Verhoeff, M. Halder, F. Peisker, G. Wiltberger, J. Bednarsch, D. Heise, J. Campello Deierl, S. Lang, , U. 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.

bioRxiv · Feb 3, 2024Cancer Biology

Cyclin B3 implements timely vertebrate oocyte arrest for fertilization

N. Bouftas, L. Schneider, M. Halder, R. Demmig, M. Baack, D. Cladiere, M. Walter, H. Al Abdallah, C. Kleinhempel, J. Mueller, F. Passarelli, P. Wehrle, A. Heim, K. Wassmann, T. U. Mayer

This study identifies cyclin B3 as essential for maintaining meiosis I arrest in oocytes by regulating Emi2 degradation, ensuring timely meiosis II arrest for fertilization.

bioRxiv · Jun 4, 2022Cell Biology

Deep learning-based molecular morphometrics for kidney biopsies

M. Zimmermann, M. Klaus, M. N. Wong, A.-K. Thebille, L. Gernhold, C. Kuppe, M. Halder, J. Kranz, N. Wanner, F. Braun, S. Wulf, T. Wiech, U. Panzer, C. F. Krebs, E. Hoxha, , V. G. Puelles

The paper develops a deep learning method for analyzing kidney biopsy images to quantify podocyte loss, identifying morphometric signatures in ANCA-GN patients for risk stratification.

bioRxiv · Aug 23, 2020Pathology