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SOAX: A software for quantification of 3D biopolymer networks

Filamentous biopolymer networks in cells and tissues are routinely imaged by confocal microscopy. Image analysis methods enable quantitative study of the properties of these curvilinear networks. However, software tools to quantify the geometry and topology of these often dense 3D networks and to lo...

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Autores principales: Xu, Ting, Vavylonis, Dimitrios, Tsai, Feng-Ching, Koenderink, Gijsje H., Nie, Wei, Yusuf, Eddy, I-Ju Lee, Wu, Jian-Qiu, Huang, Xiaolei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4357869/
https://www.ncbi.nlm.nih.gov/pubmed/25765313
http://dx.doi.org/10.1038/srep09081
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author Xu, Ting
Vavylonis, Dimitrios
Tsai, Feng-Ching
Koenderink, Gijsje H.
Nie, Wei
Yusuf, Eddy
I-Ju Lee
Wu, Jian-Qiu
Huang, Xiaolei
author_facet Xu, Ting
Vavylonis, Dimitrios
Tsai, Feng-Ching
Koenderink, Gijsje H.
Nie, Wei
Yusuf, Eddy
I-Ju Lee
Wu, Jian-Qiu
Huang, Xiaolei
author_sort Xu, Ting
collection PubMed
description Filamentous biopolymer networks in cells and tissues are routinely imaged by confocal microscopy. Image analysis methods enable quantitative study of the properties of these curvilinear networks. However, software tools to quantify the geometry and topology of these often dense 3D networks and to localize network junctions are scarce. To fill this gap, we developed a new software tool called “SOAX”, which can accurately extract the centerlines of 3D biopolymer networks and identify network junctions using Stretching Open Active Contours (SOACs). It provides an open-source, user-friendly platform for network centerline extraction, 2D/3D visualization, manual editing and quantitative analysis. We propose a method to quantify the performance of SOAX, which helps determine the optimal extraction parameter values. We quantify several different types of biopolymer networks to demonstrate SOAX's potential to help answer key questions in cell biology and biophysics from a quantitative viewpoint.
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spelling pubmed-43578692015-03-17 SOAX: A software for quantification of 3D biopolymer networks Xu, Ting Vavylonis, Dimitrios Tsai, Feng-Ching Koenderink, Gijsje H. Nie, Wei Yusuf, Eddy I-Ju Lee Wu, Jian-Qiu Huang, Xiaolei Sci Rep Article Filamentous biopolymer networks in cells and tissues are routinely imaged by confocal microscopy. Image analysis methods enable quantitative study of the properties of these curvilinear networks. However, software tools to quantify the geometry and topology of these often dense 3D networks and to localize network junctions are scarce. To fill this gap, we developed a new software tool called “SOAX”, which can accurately extract the centerlines of 3D biopolymer networks and identify network junctions using Stretching Open Active Contours (SOACs). It provides an open-source, user-friendly platform for network centerline extraction, 2D/3D visualization, manual editing and quantitative analysis. We propose a method to quantify the performance of SOAX, which helps determine the optimal extraction parameter values. We quantify several different types of biopolymer networks to demonstrate SOAX's potential to help answer key questions in cell biology and biophysics from a quantitative viewpoint. Nature Publishing Group 2015-03-13 /pmc/articles/PMC4357869/ /pubmed/25765313 http://dx.doi.org/10.1038/srep09081 Text en Copyright © 2015, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder in order to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Xu, Ting
Vavylonis, Dimitrios
Tsai, Feng-Ching
Koenderink, Gijsje H.
Nie, Wei
Yusuf, Eddy
I-Ju Lee
Wu, Jian-Qiu
Huang, Xiaolei
SOAX: A software for quantification of 3D biopolymer networks
title SOAX: A software for quantification of 3D biopolymer networks
title_full SOAX: A software for quantification of 3D biopolymer networks
title_fullStr SOAX: A software for quantification of 3D biopolymer networks
title_full_unstemmed SOAX: A software for quantification of 3D biopolymer networks
title_short SOAX: A software for quantification of 3D biopolymer networks
title_sort soax: a software for quantification of 3d biopolymer networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4357869/
https://www.ncbi.nlm.nih.gov/pubmed/25765313
http://dx.doi.org/10.1038/srep09081
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