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Stochasticity and the limits of molecular signaling in plant development
Understanding plant development is in part a theoretical endeavor that can only succeed if it is based upon a correctly contrived axiomatic framework. Here I revisit some of the basic assumptions that frame our understanding of plant development and suggest that we consider an alternative informatio...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9627605/ https://www.ncbi.nlm.nih.gov/pubmed/36340340 http://dx.doi.org/10.3389/fpls.2022.999304 |
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author | Lintilhac, Philip M. |
author_facet | Lintilhac, Philip M. |
author_sort | Lintilhac, Philip M. |
collection | PubMed |
description | Understanding plant development is in part a theoretical endeavor that can only succeed if it is based upon a correctly contrived axiomatic framework. Here I revisit some of the basic assumptions that frame our understanding of plant development and suggest that we consider an alternative informational ecosystem that more faithfully reflects the physical and architectural realities of plant tissue and organ growth. I discuss molecular signaling as a stochastic process and propose that the iterative and architectural nature of plant growth is more usefully represented by deterministic models based upon structural, surficial, and stress-mechanical information networks that come into play at the trans-cellular level. |
format | Online Article Text |
id | pubmed-9627605 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96276052022-11-03 Stochasticity and the limits of molecular signaling in plant development Lintilhac, Philip M. Front Plant Sci Plant Science Understanding plant development is in part a theoretical endeavor that can only succeed if it is based upon a correctly contrived axiomatic framework. Here I revisit some of the basic assumptions that frame our understanding of plant development and suggest that we consider an alternative informational ecosystem that more faithfully reflects the physical and architectural realities of plant tissue and organ growth. I discuss molecular signaling as a stochastic process and propose that the iterative and architectural nature of plant growth is more usefully represented by deterministic models based upon structural, surficial, and stress-mechanical information networks that come into play at the trans-cellular level. Frontiers Media S.A. 2022-10-19 /pmc/articles/PMC9627605/ /pubmed/36340340 http://dx.doi.org/10.3389/fpls.2022.999304 Text en Copyright © 2022 Lintilhac https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Lintilhac, Philip M. Stochasticity and the limits of molecular signaling in plant development |
title | Stochasticity and the limits of molecular signaling in plant development |
title_full | Stochasticity and the limits of molecular signaling in plant development |
title_fullStr | Stochasticity and the limits of molecular signaling in plant development |
title_full_unstemmed | Stochasticity and the limits of molecular signaling in plant development |
title_short | Stochasticity and the limits of molecular signaling in plant development |
title_sort | stochasticity and the limits of molecular signaling in plant development |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9627605/ https://www.ncbi.nlm.nih.gov/pubmed/36340340 http://dx.doi.org/10.3389/fpls.2022.999304 |
work_keys_str_mv | AT lintilhacphilipm stochasticityandthelimitsofmolecularsignalinginplantdevelopment |