期刊
BIOINFORMATICS
卷 30, 期 22, 页码 3291-3292出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btu503
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资金
- Max Planck Society
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.
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