CytoSeg 2.0: automated extraction of actin filaments

Jacqueline Nowak; Kristin Gennermann; Staffan Persson; Zoran Nikoloski

doi:10.1093/bioinformatics/btaa035

CytoSeg 2.0: automated extraction of actin filaments

Bioinformatics. 2020 May 1;36(9):2950-2951. doi: 10.1093/bioinformatics/btaa035.

Authors

Jacqueline Nowak^{1

2

3}, Kristin Gennermann², Staffan Persson¹, Zoran Nikoloski^{2

3}

Affiliations

¹ School of Biosciences, University of Melbourne, Parkville, VIC 3010, Australia.
² Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam, 14476 Potsdam, Germany.
³ Systems Biology and Mathematical Modeling, Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam, Germany.

Abstract

Motivation: Actin filaments (AFs) are dynamic structures that substantially change their organization over time. The dynamic behavior and the relatively low signal-to-noise ratio during live-cell imaging have rendered the quantification of the actin organization a difficult task.

Results: We developed an automated image-based framework that extracts AFs from fluorescence microscopy images and represents them as networks, which are automatically analyzed to identify and compare biologically relevant features. Although the source code is freely available, we have now implemented the framework into a graphical user interface that can be installed as a Fiji plugin, thus enabling easy access by the research community.

Availability and implementation: CytoSeg 2.0 is open-source software under the GPL and is available on Github: https://github.com/jnowak90/CytoSeg2.0.

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Actin Cytoskeleton
Research Design*
Signal-To-Noise Ratio
Software*