ArticleNature communications2021
A network-based framework for shape analysis enables accurate characterization of leaf epidermal cells.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Image-Based Quantitative Analysis of Epidermal Morphology in Wild Potato Leaves.Plants (Basel, Switzerland) · 2024Article
- Hierarchical global and local auxin signals coordinate cellular interdigitation inbioRxiv : the preprint server for biology · 2024Article
- Seed shape and size ofFrontiers in plant science · 2024Article
- Plantorganelle Hunter is an effective deep-learning-based method for plant organelle phenotyping in electron microscopy.Nature plants · 2023Article
- Mechano-chemical regulation of complex cell shape formation: Epidermal pavement cells-A case study.Quantitative plant biology · 2023Review
- No cell is an island: characterising the leaf epidermis using epidermalmorph, a new R package.The New phytologist · 2023Article
- Topological properties accurately predict cell division events and organization of shoot apical meristem in Arabidopsis thaliana.Development (Cambridge, England) · 2022Article
- Using quantitative methods to understand leaf epidermal development.Quantitative plant biology · 2022Review
- CuticleTrace: A toolkit for capturing cell outlines from leaf cuticle with implications for paleoecology and paleoclimatology.Applications in plant sciencesArticle
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.