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AmoePy

Name: AmoePy
Keywords: cell migration, fluorescence imaging, cell motility, Dictyostelium discoideum, social amoeba, simulation, cell segmentation, amoeboid motion, data assimilation, mathematical model

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 20 Aug 2021 English Publisher:ZenodoFunded by:DFG | unidentified

Authors: Daniel Schindler; Ted Moldenhawer; Lena Lindenmeier; Victor Lesur; Matthias Holschneider;

doi: 10.5281/zenodo.5227407 , 10.5281/zenodo.15098663 , 10.5281/zenodo.3982371 , 10.5281/zenodo.7539065 , 10.5281/zenodo.6588428 , 10.5281/zenodo.7391145 , 10.5281/zenodo.7275105 , 10.5281/zenodo.15066706

AmoePy

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Abstract

\(\Large\textrm{Deprecated.}\) New version under this Link ___________________________________________________________ A Python-based toolbox for analyzing and simulating amoeboid cell motility. Furthermore, this publication contains two-dimensional cell contour data segmented from the following microscopy data: Dictyostelium discoideum (fluorescence microscopy): Link Fundulus heteroclitus (fluorescence microscopy): Link1, Link2, Link3 Hypsophrys nicaraguensis (bright-field microscopy): Link (Movie S1-S4) The segmentation routines in AmoePy are a modified version of the active contour (snake) algorithm described in [1] and [2] This Project is part of the Collaborative Research Center SFB 1294 (Project: B02).

The research of this project has been partially funded by the Deutsche Forschungsgemeinschaft (DFG) Project-ID 318763901 - SFB1294.

Related Organizations

University of Potsdam
Germany

Keywords

cell migration, fluorescence imaging, cell motility, Dictyostelium discoideum, social amoeba, simulation, cell segmentation, amoeboid motion, data assimilation, mathematical model, Python, microscopy data

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Fluorescent (C)LSM image sequences of Dictyostelium discoideum (Ax2 - LifeAct mRFP) for cell track and cell contour analysis
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