Cell Systems Dynamics Group

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Software

We share and open-source published software developed in our group:

IMG

Schirmacher D, Armagan Ü, Zhang Y, Kull T, Auler M and Schroeder T (2024)
aiSEGcell: user-friendly deep learning-based segmentation of nuclei in transmitted light images
PLOS Computational Biology, 20(8):e1012361

aiSEGcell

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Wehling A, Loeffler D, Zhang Y, Kull T, Donato C, Szczerba B, Ortega GC, Lee M, Moor A, Göttgens B, Aceto N. and Schroeder T (2022)
 Combined single-cell tracking and omics improves blood stem cell fate regulator identification.
Blood. 10.1182/blood.2022016880

trackSeq

alerT

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Kunz L and Schroeder T (2019)
A 3D tissue-​wide digital imaging pipeline for quantitation of secreted molecules shows absence of CXCL12 gradients in bone marrow
Cell Stem Cell, 25(6):846-​854

DDD

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Coutu DL, Kokkaliaris KD, Kunz L and Schroeder T (2018)
Multicolor quantitative confocal imaging cytometry
Nature Methods, 15: 39-46

XiT

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Hilsenbeck O, Schwarzfischer M, Loeffler D, Dimopoulos S, Hastreiter S, Marr C, Theis FJ and Schroeder T (2017)
fastER: a user-friendly tool for ultrafast and robust cell segmentation in large-scale microscopy
Bioinformatics, 33: 2020-2028

fastER

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Hilsenbeck O*, Schwarzfischer M*, Skylaki S*, Schauberger B, Hoppe PS, Loeffler D, Kokkaliaris KD, Hastreiter S, Skylaki E, Filipczyk A, Strasser M, Buggenthin F, Feigelman JS, Krumsiek J, van den Berg AJJ, Endele M, Etzrodt M, Marr C, Theis FJ* and Schroeder T* (2016)
Software tools for single-cell tracking and quantification of cellular and molecular properties
Nature Biotechnology, 34: 703-706

tTt and qTfy