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Noise and Robustness in Phyllotaxis

Overview of attention for article published in PLoS Computational Biology, February 2012
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Title
Noise and Robustness in Phyllotaxis
Published in
PLoS Computational Biology, February 2012
DOI 10.1371/journal.pcbi.1002389
Pubmed ID
Authors

Vincent Mirabet, Fabrice Besnard, Teva Vernoux, Arezki Boudaoud

Abstract

A striking feature of vascular plants is the regular arrangement of lateral organs on the stem, known as phyllotaxis. The most common phyllotactic patterns can be described using spirals, numbers from the Fibonacci sequence and the golden angle. This rich mathematical structure, along with the experimental reproduction of phyllotactic spirals in physical systems, has led to a view of phyllotaxis focusing on regularity. However all organisms are affected by natural stochastic variability, raising questions about the effect of this variability on phyllotaxis and the achievement of such regular patterns. Here we address these questions theoretically using a dynamical system of interacting sources of inhibitory field. Previous work has shown that phyllotaxis can emerge deterministically from the self-organization of such sources and that inhibition is primarily mediated by the depletion of the plant hormone auxin through polarized transport. We incorporated stochasticity in the model and found three main classes of defects in spiral phyllotaxis--the reversal of the handedness of spirals, the concomitant initiation of organs and the occurrence of distichous angles--and we investigated whether a secondary inhibitory field filters out defects. Our results are consistent with available experimental data and yield a prediction of the main source of stochasticity during organogenesis. Our model can be related to cellular parameters and thus provides a framework for the analysis of phyllotactic mutants at both cellular and tissular levels. We propose that secondary fields associated with organogenesis, such as other biochemical signals or mechanical forces, are important for the robustness of phyllotaxis. More generally, our work sheds light on how a target pattern can be achieved within a noisy background.

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Geographical breakdown

Country Count As %
France 3 4%
Portugal 1 1%
Switzerland 1 1%
United Kingdom 1 1%
Argentina 1 1%
United States 1 1%
Unknown 75 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 29%
Student > Ph. D. Student 14 17%
Student > Master 14 17%
Professor 6 7%
Professor > Associate Professor 6 7%
Other 8 10%
Unknown 11 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 46 55%
Biochemistry, Genetics and Molecular Biology 6 7%
Physics and Astronomy 6 7%
Computer Science 2 2%
Engineering 2 2%
Other 10 12%
Unknown 11 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 February 2012.
All research outputs
#19,962,154
of 25,394,764 outputs
Outputs from PLoS Computational Biology
#7,956
of 8,964 outputs
Outputs of similar age
#128,327
of 167,826 outputs
Outputs of similar age from PLoS Computational Biology
#88
of 116 outputs
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