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Identification of approximate symmetries in biological development

Virtually all forms of life, from single-cell eukaryotes to complex, highly differentiated multicellular organisms, exhibit a property referred to as symmetry. However, precise measures of symmetry are often difficult to formulate and apply in a meaningful way to biological systems, where symmetries...

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Detalles Bibliográficos
Autores principales: Gandhi, Punit, Ciocanel, Maria-Veronica, Niklas, Karl, Dawes, Adriana T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8580469/
https://www.ncbi.nlm.nih.gov/pubmed/34743597
http://dx.doi.org/10.1098/rsta.2020.0273
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author Gandhi, Punit
Ciocanel, Maria-Veronica
Niklas, Karl
Dawes, Adriana T.
author_facet Gandhi, Punit
Ciocanel, Maria-Veronica
Niklas, Karl
Dawes, Adriana T.
author_sort Gandhi, Punit
collection PubMed
description Virtually all forms of life, from single-cell eukaryotes to complex, highly differentiated multicellular organisms, exhibit a property referred to as symmetry. However, precise measures of symmetry are often difficult to formulate and apply in a meaningful way to biological systems, where symmetries and asymmetries can be dynamic and transient, or be visually apparent but not reliably quantifiable using standard measures from mathematics and physics. Here, we present and illustrate a novel measure that draws on concepts from information theory to quantify the degree of symmetry, enabling the identification of approximate symmetries that may be present in a pattern or a biological image. We apply the measure to rotation, reflection and translation symmetries in patterns produced by a Turing model, as well as natural objects (algae, flowers and leaves). This method of symmetry quantification is unbiased and rigorous, and requires minimal manual processing compared to alternative measures. The proposed method is therefore a useful tool for comparison and identification of symmetries in biological systems, with potential future applications to symmetries that arise during development, as observed in vivo or as produced by mathematical models. This article is part of the theme issue ‘Recent progress and open frontiers in Turing’s theory of morphogenesis’.
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spelling pubmed-85804692022-02-02 Identification of approximate symmetries in biological development Gandhi, Punit Ciocanel, Maria-Veronica Niklas, Karl Dawes, Adriana T. Philos Trans A Math Phys Eng Sci Articles Virtually all forms of life, from single-cell eukaryotes to complex, highly differentiated multicellular organisms, exhibit a property referred to as symmetry. However, precise measures of symmetry are often difficult to formulate and apply in a meaningful way to biological systems, where symmetries and asymmetries can be dynamic and transient, or be visually apparent but not reliably quantifiable using standard measures from mathematics and physics. Here, we present and illustrate a novel measure that draws on concepts from information theory to quantify the degree of symmetry, enabling the identification of approximate symmetries that may be present in a pattern or a biological image. We apply the measure to rotation, reflection and translation symmetries in patterns produced by a Turing model, as well as natural objects (algae, flowers and leaves). This method of symmetry quantification is unbiased and rigorous, and requires minimal manual processing compared to alternative measures. The proposed method is therefore a useful tool for comparison and identification of symmetries in biological systems, with potential future applications to symmetries that arise during development, as observed in vivo or as produced by mathematical models. This article is part of the theme issue ‘Recent progress and open frontiers in Turing’s theory of morphogenesis’. The Royal Society 2021-12-27 2021-11-08 /pmc/articles/PMC8580469/ /pubmed/34743597 http://dx.doi.org/10.1098/rsta.2020.0273 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Articles
Gandhi, Punit
Ciocanel, Maria-Veronica
Niklas, Karl
Dawes, Adriana T.
Identification of approximate symmetries in biological development
title Identification of approximate symmetries in biological development
title_full Identification of approximate symmetries in biological development
title_fullStr Identification of approximate symmetries in biological development
title_full_unstemmed Identification of approximate symmetries in biological development
title_short Identification of approximate symmetries in biological development
title_sort identification of approximate symmetries in biological development
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8580469/
https://www.ncbi.nlm.nih.gov/pubmed/34743597
http://dx.doi.org/10.1098/rsta.2020.0273
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