ReviewFrontiers in plant science2014
Quantification of variability in trichome patterns.
Review in Frontiers in plant science, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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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.
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Who cites it
10 citing papers in PubMed, 17 citations in OpenAlex.
- Spatial ploidy inference using quantitative imaging.Cell reports methods · 2025Article
- A common pathway controls cell size in the sepal and leaf epidermis leading to a nonrandom pattern of giant cells.PLoS biology · 2025Article
- What Is a Plant Cell Type in the Age of Single-Cell Biology? It's Complicated.Annual review of cell and developmental biology · 2024Review
- Stochastic Turing patterns of trichomes inProceedings of the National Academy of Sciences of the United States of America · 2023Article
- Using quantitative methods to understand leaf epidermal development.Quantitative plant biology · 2022Review
- Leaf Trichome Distribution Pattern inPlants (Basel, Switzerland) · 2020Article
- The Dynamic Genetic-Hormonal Regulatory Network Controlling the Trichome Development in Leaves.Plants (Basel, Switzerland) · 2019Review
- Article
- Fluctuations of the transcription factor ATML1 generate the pattern of giant cells in theeLife · 2017Article
- Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
While pattern formation is studied in various areas of biology, little is known about the noise leading to variations between individual realizations of the pattern. One prominent example for de novo pattern formation in plants is the patterning of trichomes on Arabidopsis leaves, which involves genetic regulation and cell-to-cell communication. These processes are potentially variable due to, e.g., the abundance of cell components or environmental conditions. To elevate the understanding of regulatory processes underlying the pattern formation it is crucial to quantitatively analyze the variability in naturally occurring patterns. Here, we review recent approaches toward characterization of noise on trichome initiation. We present methods for the quantification of spatial patterns, which are the basis for data-driven mathematical modeling and enable the analysis of noise from different sources. Besides the insight gained on trichome formation, the examination of observed trichome patterns also shows that highly regulated biological processes can be substantially affected by variability.
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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.