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img2net: automated network-based analysis of imaged phenotypes

机译:img2net:基于网络的图像表型自动分析

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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.
机译:成像表型的自动分析可对生物学相关特征进行快速且可重复的定量。尽管有最新进展,但复杂的网络结构(例如叶脉模式,细胞骨架结构或交通网络)的记录仍然难以分析。在这里,我们说明了img2net通过重构底层网络,计算相关网络属性并统计比较不同类型或不同条件下的网络来自动分析此类结构的适用性。该软件可轻松用于分析任意2D和3D网络状结构的图像数据。

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