KIT | KIT-Bibliothek | Impressum | Datenschutz

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

Schott, Benjamin; Traub, Manuel; Schlagenhauf, Cornelia; Takamiya, Masanari; Antritter, Thomas; Bartschat, Andreas; Löffler, Katharina; Blessing, Denis; Otte, Jens C.; Kobitski, Andrei Y.; Nienhaus, G. Ulrich; Strähle, Uwe; Mikut, Ralf; Stegmaier, Johannes

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.

Open Access Logo

Verlagsausgabe §
DOI: 10.5445/IR/1000082328
Veröffentlicht am 02.05.2018
DOI: 10.1371/journal.pcbi.1006128
Zitationen: 3
Web of Science
Zitationen: 1
Zugehörige Institution(en) am KIT Institut für Toxikologie und Genetik (ITG)
Institut für Nanotechnologie (INT)
Institut für Automation und angewandte Informatik (IAI)
Publikationstyp Zeitschriftenaufsatz
Jahr 2018
Sprache Englisch
Identifikator ISSN: 1553-734X, 1553-7358
KITopen-ID: 1000082328
HGF-Programm 47.01.02 (POF III, LK 01)
Erschienen in PLoS Computational Biology
Band 14
Heft 4
Seiten e1006128
Bemerkung zur Veröffentlichung Gefördert durch den KIT-Publikationsfonds
Nachgewiesen in Scopus
Web of Science
KIT – Die Forschungsuniversität in der Helmholtz-Gemeinschaft
KITopen Landing Page