SOAX: A software for quantification of 3D biopolymer networks

Ting Xu, Dimitrios Vavylonis, Feng Ching Tsai, Gijsje H. Koenderink, Wei Nie, Eddy Yusuf, I. Ju Lee, Jian Qiu Wu, Xiaolei Huang

Research output: Contribution to journalArticlepeer-review

35 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article number9081
JournalScientific reports
Volume5
DOIs
StatePublished - 2015

All Science Journal Classification (ASJC) codes

  • General

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