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CytoSeg 2.0

  • 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.

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Author details:Jacqueline NowakORCiDGND, Kristin Gennermann, Staffan PerssonORCiDGND, Zoran NikoloskiORCiDGND
DOI:https://doi.org/10.1093/bioinformatics/btaa035
ISSN:1367-4803
ISSN:1460-2059
Pubmed ID:https://pubmed.ncbi.nlm.nih.gov/31971582
Title of parent work (English):Bioinformatics
Subtitle (English):automated extraction of actin filaments
Publisher:Oxford Univ. Press
Place of publishing:Oxford
Publication type:Article
Language:English
Date of first publication:2020/01/23
Publication year:2020
Release date:2023/07/13
Volume:36
Issue:9
Number of pages:2
First page:2950
Last Page:2951
Funding institution:German Federal Ministry of Research and Education project SHAPENET; [031L0177A]; Australian Research CouncilAustralian Research Council; [DP19001941, FT160100218]; IRRTF grant from the University of Melbourne
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Biochemie und Biologie
DDC classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Peer review:Referiert
Publishing method:Open Access / Hybrid Open-Access
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License (German):License LogoCC-BY - Namensnennung 4.0 International
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