img2net: Automated network-based analysis of imaged phenotypes
Abstract
Automated analysis of imaged phenotypes enables fast and reproducible quantification of biologically relevant features. Despite recent developments, recordings of complex, networked structures, such as: leaf venation patterns, cytoskeletal structures, or traffic networks, remain challenging to analyze. Here we illustrate the applicability of img2net to automatedly analyze such structures by reconstructing the underlying network, computing relevant network properties, and statistically comparing networks of different types or under different conditions. The software can be readily used for analyzing image data of arbitrary 2D and 3D network-like structures. img2net is open-source software under the GPL and can be downloaded from http://mathbiol.mpimp-golm.mpg.de/img2net/, where supplementary information and data sets for testing are provided.
Keywords
Cite
@article{arxiv.1507.02996,
title = {img2net: Automated network-based analysis of imaged phenotypes},
author = {David Breuer and Zoran Nikoloski},
journal= {arXiv preprint arXiv:1507.02996},
year = {2017}
}
Comments
Bioinformatics, 2014, btu503