PUBLICATION

EmbryoMiner: A new framework for interactive knowledge discovery in large-scale cell tracking data of developing embryos

Authors
Schott, B., Traub, M., Schlagenhauf, C., Takamiya, M., Antritter, T., Bartschat, A., Löffler, K., Blessing, D., Otte, J.C., Kobitski, A.Y., Nienhaus, G.U., Strähle, U., Mikut, R., Stegmaier, J.
ID
ZDB-PUB-180421-10
Date
2018
Source
PLoS Computational Biology   14: e1006128 (Journal)
Registered Authors
Mikut, Ralf, Otte, Jens, Strähle, Uwe, Takamiya, Masanari
Keywords
none
MeSH Terms
  • Software
  • Computational Biology
  • Gastrulation
  • Imaging, Three-Dimensional
  • Animals
  • Cell Movement
  • Animals, Genetically Modified
  • Embryonic Development
  • Microscopy, Fluorescence
  • Embryonic Stem Cells/cytology
  • Olfactory Mucosa/cytology
  • Olfactory Mucosa/embryology
  • Germ Layers/cytology
  • Cell Tracking/statistics & numerical data*
  • Zebrafish/embryology*
(all 15)
PubMed
29672531 Full text @ PLoS Comput. Biol.
Abstract
State-of-the-art light-sheet and confocal microscopes allow recording of entire embryos in 3D and over time (3D+t) for many hours. Fluorescently labeled structures can be segmented and tracked automatically in these terabyte-scale 3D+t images, resulting in thousands of cell migration trajectories that provide detailed insights to large-scale tissue reorganization at the cellular level. Here we present EmbryoMiner, a new interactive open-source framework suitable for in-depth analyses and comparisons of entire embryos, including an extensive set of trajectory features. Starting at the whole-embryo level, the framework can be used to iteratively focus on a region of interest within the embryo, to investigate and test specific trajectory-based hypotheses and to extract quantitative features from the isolated trajectories. Thus, the new framework provides a valuable new way to quantitatively compare corresponding anatomical regions in different embryos that were manually selected based on biological prior knowledge. As a proof of concept, we analyzed 3D+t light-sheet microscopy images of zebrafish embryos, showcasing potential user applications that can be performed using the new framework.
Genes / Markers
Figures
Figure Gallery (7 images)
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Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Antibodies
Orthology
Engineered Foreign Genes
Mapping
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Citation
Schott, B., Traub, M., Schlagenhauf, C., Takamiya, M., Antritter, T., Bartschat, A., Löffler, K., Blessing, D., Otte, J.C., Kobitski, A.Y., Nienhaus, G.U., Strähle, U., Mikut, R., Stegmaier, J. (2018) EmbryoMiner: A new framework for interactive knowledge discovery in large-scale cell tracking data of developing embryos. PLoS Computational Biology. 14:e1006128.