Author
Listed:
- Jacqueline Nowak
(University of Melbourne
University of Potsdam
Systems Biology and Mathematical Modelling, Max Planck Institute of Molecular Plant Physiology)
- Ryan Christopher Eng
(Plant Cell Biology and Microscopy, Max Planck Institute of Molecular Plant Physiology)
- Timon Matz
(University of Potsdam
Systems Biology and Mathematical Modelling, Max Planck Institute of Molecular Plant Physiology)
- Matti Waack
(University of Potsdam
Systems Biology and Mathematical Modelling, Max Planck Institute of Molecular Plant Physiology)
- Staffan Persson
(University of Melbourne
Shanghai Jiao Tong University
University of Copenhagen
University of Copenhagen)
- Arun Sampathkumar
(Plant Cell Biology and Microscopy, Max Planck Institute of Molecular Plant Physiology)
- Zoran Nikoloski
(University of Potsdam
Systems Biology and Mathematical Modelling, Max Planck Institute of Molecular Plant Physiology)
Abstract
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.
Suggested Citation
Jacqueline Nowak & Ryan Christopher Eng & Timon Matz & Matti Waack & Staffan Persson & Arun Sampathkumar & Zoran Nikoloski, 2021.
"A network-based framework for shape analysis enables accurate characterization of leaf epidermal cells,"
Nature Communications, Nature, vol. 12(1), pages 1-13, December.
Handle:
RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-020-20730-y
DOI: 10.1038/s41467-020-20730-y
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