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Turing pattern design principles and their robustness

Turing patterns have morphed from mathematical curiosities into highly desirable targets for synthetic biology. For a long time, their biological significance was sometimes disputed but there is now ample evidence for their involvement in processes ranging from skin pigmentation to digit and limb fo...

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Autores principales: Vittadello, Sean T., Leyshon, Thomas, Schnoerr, David, Stumpf, Michael P. H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8580431/
https://www.ncbi.nlm.nih.gov/pubmed/34743598
http://dx.doi.org/10.1098/rsta.2020.0272
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author Vittadello, Sean T.
Leyshon, Thomas
Schnoerr, David
Stumpf, Michael P. H.
author_facet Vittadello, Sean T.
Leyshon, Thomas
Schnoerr, David
Stumpf, Michael P. H.
author_sort Vittadello, Sean T.
collection PubMed
description Turing patterns have morphed from mathematical curiosities into highly desirable targets for synthetic biology. For a long time, their biological significance was sometimes disputed but there is now ample evidence for their involvement in processes ranging from skin pigmentation to digit and limb formation. While their role in developmental biology is now firmly established, their synthetic design has so far proved challenging. Here, we review recent large-scale mathematical analyses that have attempted to narrow down potential design principles. We consider different aspects of robustness of these models and outline why this perspective will be helpful in the search for synthetic Turing-patterning systems. We conclude by considering robustness in the context of developmental modelling more generally. 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-85804312022-02-02 Turing pattern design principles and their robustness Vittadello, Sean T. Leyshon, Thomas Schnoerr, David Stumpf, Michael P. H. Philos Trans A Math Phys Eng Sci Articles Turing patterns have morphed from mathematical curiosities into highly desirable targets for synthetic biology. For a long time, their biological significance was sometimes disputed but there is now ample evidence for their involvement in processes ranging from skin pigmentation to digit and limb formation. While their role in developmental biology is now firmly established, their synthetic design has so far proved challenging. Here, we review recent large-scale mathematical analyses that have attempted to narrow down potential design principles. We consider different aspects of robustness of these models and outline why this perspective will be helpful in the search for synthetic Turing-patterning systems. We conclude by considering robustness in the context of developmental modelling more generally. 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/PMC8580431/ /pubmed/34743598 http://dx.doi.org/10.1098/rsta.2020.0272 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
Vittadello, Sean T.
Leyshon, Thomas
Schnoerr, David
Stumpf, Michael P. H.
Turing pattern design principles and their robustness
title Turing pattern design principles and their robustness
title_full Turing pattern design principles and their robustness
title_fullStr Turing pattern design principles and their robustness
title_full_unstemmed Turing pattern design principles and their robustness
title_short Turing pattern design principles and their robustness
title_sort turing pattern design principles and their robustness
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8580431/
https://www.ncbi.nlm.nih.gov/pubmed/34743598
http://dx.doi.org/10.1098/rsta.2020.0272
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