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Sci Rep. 2019 Feb 8;9(1):1717. doi: 10.1038/s41598-018-37182-6.

Automated Tracking of Biopolymer Growth and Network Deformation with TSOAX.

Author information

1
Department of Computer Science and Engineering, Lehigh University, Bethlehem, PA, 18015, USA.
2
Department of Physics, Lehigh University, Bethlehem, PA, 18015, USA.
3
AMOLF, Living Matter Department, 1098 XG, Amsterdam, The Netherlands.
4
Department of Molecular Genetics, The Ohio State University, Columbus, OH, 43210, USA.
5
Howard Hughes Medical Institute and Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA.
6
Department of Computer Science and Engineering, Lehigh University, Bethlehem, PA, 18015, USA. suh972@ist.psu.edu.
7
College of Information Sciences and Technology, Penn State University, University Park, PA, 16802, USA. suh972@ist.psu.edu.
8
Department of Physics, Lehigh University, Bethlehem, PA, 18015, USA. vavylonis@lehigh.edu.

Abstract

Studies of how individual semi-flexible biopolymers and their network assemblies change over time reveal dynamical and mechanical properties important to the understanding of their function in tissues and living cells. Automatic tracking of biopolymer networks from fluorescence microscopy time-lapse sequences facilitates such quantitative studies. We present an open source software tool that combines a global and local correspondence algorithm to track biopolymer networks in 2D and 3D, using stretching open active contours. We demonstrate its application in fully automated tracking of elongating and intersecting actin filaments, detection of loop formation and constriction of tilted contractile rings in live cells, and tracking of network deformation under shear deformation.

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