School of Biosciences, University of Melbourne, Parkville, VIC, 3010, Australia.
Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam, 14476, Potsdam, Germany.
Nat Commun. 2021 Jan 19;12(1):458. doi: 10.1038/s41467-020-20730-y.
Cell shape is crucial for the function and development of organisms. Yet, versatile frameworks for cell shape quantification, comparison, and classification remain underdeveloped. Here, we introduce a visibility graph representation of shapes that facilitates network-driven characterization and analyses across shapes encountered in different domains. Using the example of complex shape of leaf pavement cells, we show that our framework accurately quantifies cell protrusions and invaginations and provides additional functionality in comparison to the contending approaches. We further show that structural properties of the visibility graphs can be used to quantify pavement cell shape complexity and allow for classification of plants into their respective phylogenetic clades. Therefore, the visibility graphs provide a robust and unique framework to accurately quantify and classify the shape of different objects.
细胞形状对于生物体的功能和发育至关重要。然而，用于细胞形状定量、比较和分类的多功能框架仍未得到充分发展。在这里，我们引入了一种形状的可见性图表示法，该表示法有助于在不同领域遇到的形状中进行网络驱动的特征描述和分析。我们以叶片平铺细胞的复杂形状为例，展示了我们的框架如何准确地量化细胞的突起和内陷，并与竞争方法相比提供了额外的功能。我们进一步表明，可见性图的结构性质可用于量化平铺细胞形状的复杂性，并允许根据其各自的系统发育分支对植物进行分类。因此，可见性图为准确地量化和分类不同物体的形状提供了一个强大而独特的框架。
