Sign in
Developmental BiologyDevelopment Genes and Evolution
Peer-reviewed journal article

BioCell2XML: A novel tool for converting cell lineage data from SIMI BioCell to MaMuT (Fiji)

Markus Pennerstorfer, Günther LooseiD, Carsten WolffiD

Abstract

Computer-assisted 4D manual cell tracking has been a valuable method for understanding spatial-temporal dynamics of embryogenesis (e.g., Stach & Anselmi, 2015; Vellutini et al., 2017; Wolff et al., 2018) since the method was introduced in the late 1990s. Since two decades SIMI(R) BioCell (Schnabel et al., 1997), a software which initially was developed for analyzing data coming from the, at that time new technique of 4D microscopy, is in use. Many laboratories around the world use SIMI BioCell for the manual tracing of cells in embryonic development of various species to reconstruct cell genealogies with high precision. However, the software has several disadvantages: Limits in handling very large data sets, the virtually no maintenance over the last ten years (bound to older Windows versions), the difficulty to access the created cell lineage data for analyses outside SIMI BioCell, and the high cost of the program. Recently, bioinformatics, in close collaboration with biologists, developed new lineaging tools that are freely available through the open source image processing platform Fiji. Here we introduce a software tool that allows conversion of SIMI BioCell lineage data to a format that is compatible with the Fiji plugin MaMuT (Wolff et al., 2018). Hereby we intend to maintain the usability of SIMI BioCell created cell lineage data for the future and, for investigators who wish to do so, facilitate the transition from this software to a more convenient program.

02 /Specification & Classification

Click any tag to browse matching papers
Citations
0
FWCI
0.00
Field percentile
7th percentile

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISGirstmair '26Qureshi '20Salvador‐Ma '21Huijben '25Wang '26Seidel '26
55% semantic matchBioinformatics
Johannes Girstmair, Tobias Pietzsch, Vladimír Ulman+9 more·Development·Oct 7, 2026· 5 citations