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A network-based framework for shape analysis enables accurate characterization of leaf epidermal cells

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 anal...

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Detalles Bibliográficos
Autores principales: Nowak, Jacqueline, Eng, Ryan Christopher, Matz, Timon, Waack, Matti, Persson, Staffan, Sampathkumar, Arun, Nikoloski, Zoran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7815848/
https://www.ncbi.nlm.nih.gov/pubmed/33469016
http://dx.doi.org/10.1038/s41467-020-20730-y
Descripción
Sumario: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.