Author

J. Stegmaier

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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Cell Biology· 3

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 3 Approach:deep learning· 2 Assay:fluorescence / live-cell microscopy· 2 Organism:human· 2 Assay:imaging· 2 Research Focus:trajectory inference· 2 Research Focus:cell signaling & trafficking· 1 Research Focus:clustering· 1

Frequent Co-Authors

A. Bhattacharyya· 1 shared A. Bönsch· 1 shared A. Jose· 1 shared A. Scheufen· 1 shared D. Moreno-Andres· 1 shared J. Di Russo· 1 shared M. Scholkemper· 1 shared N. Schwarz· 1 shared

Activity by Year

2021-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 18 mutual co-author links

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1 shared paperCell Biology

A. Bhattacharyya

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Identification of Mitosis Stages Using Artificial Neural Networks for 3D Time Lapse Cell Sequences

T. Dincer, J. Stegmaier, A. Jose

This study uses 3D CNN models to classify mitosis stages in 3D time-lapse cell sequences, achieving higher accuracy than previous methods.

bioRxiv · Feb 12, 2024 · PreprintCell Biology

Quantitative Mapping of Keratin Networks in 3D

R. Windoffer, N. Schwarz, S. Yoon, T. Piskova, M. Scholkemper, J. Stegmaier, A. Bönsch, J. Di Russo, R. Leube

This paper develops a workflow to model and analyze the 3D organization of keratin intermediate filaments in epithelial cells using super-resolution imaging and virtual reality.

bioRxiv · Dec 6, 2021Cell Biology

LiveCellMiner: A New Tool to Analyze Mitotic Progression

D. Moreno-Andres, A. Bhattacharyya, A. Scheufen, J. Stegmaier

LiveCellMiner is a flexible open-source tool for analyzing mitotic progression using live-cell imaging data, enabling automated extraction and visualization of time-resolved features across diverse datasets.

bioRxiv · Nov 17, 2021 · PreprintCell Biology