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Tytuł pozycji:

Identification of approximate symmetries in biological development.

Tytuł:
Identification of approximate symmetries in biological development.
Autorzy:
Gandhi P; Department of Mathematics and Applied Mathematics, Virginia Commonwealth University, Richmond, VA, USA.
Ciocanel MV; Department of Mathematics and Department of Biology, Duke University, Durham, NC, USA.
Niklas K; School of Integrative Plant Biology, Cornell University, Ithaca, NY, USA.
Dawes AT; Department of Mathematics and Department of Molecular Genetics, The Ohio State University, Columbus, OH, USA.
Źródło:
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences [Philos Trans A Math Phys Eng Sci] 2021 Dec 27; Vol. 379 (2213), pp. 20200273. Date of Electronic Publication: 2021 Nov 08.
Typ publikacji:
Journal Article
Język:
English
Imprint Name(s):
Original Publication: London : The Royal Society, c1996-
MeSH Terms:
Models, Theoretical*
Physics*
Mathematics ; Models, Biological ; Morphogenesis ; Plants
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Contributed Indexing:
Keywords: approximate symmetries; asymmetry measure; information theory and entropy; morphogenesis
Entry Date(s):
Date Created: 20211108 Date Completed: 20211109 Latest Revision: 20240405
Update Code:
20240405
PubMed Central ID:
PMC8580469
DOI:
10.1098/rsta.2020.0273
PMID:
34743597
Czasopismo naukowe
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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