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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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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. |
format | Online Article Text |
id | pubmed-4357869 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
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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