Robust morphogenesis by chaotic dynamics

This research illustrates that complex dynamics of gene products enable the creation of any prescribed cellular differentiation patterns. These complex dynamics can take the form of chaotic, stochastic, or noisy chaotic dynamics. Based on this outcome and previous research, it is established that a...

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Autores principales: Reinitz, J., Vakulenko, S., Sudakow, I., Grigoriev, D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10170119/
https://www.ncbi.nlm.nih.gov/pubmed/37160971
http://dx.doi.org/10.1038/s41598-023-34041-x
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author Reinitz, J.
Vakulenko, S.
Sudakow, I.
Grigoriev, D.
author_facet Reinitz, J.
Vakulenko, S.
Sudakow, I.
Grigoriev, D.
author_sort Reinitz, J.
collection PubMed
description This research illustrates that complex dynamics of gene products enable the creation of any prescribed cellular differentiation patterns. These complex dynamics can take the form of chaotic, stochastic, or noisy chaotic dynamics. Based on this outcome and previous research, it is established that a generic open chemical reactor can generate an exceptionally large number of different cellular patterns. The mechanism of pattern generation is robust under perturbations and it is based on a combination of Turing’s machines, Turing instability and L. Wolpert’s gradients. These results can help us to explain the formidable adaptive capacities of biochemical systems.
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spelling pubmed-101701192023-05-11 Robust morphogenesis by chaotic dynamics Reinitz, J. Vakulenko, S. Sudakow, I. Grigoriev, D. Sci Rep Article This research illustrates that complex dynamics of gene products enable the creation of any prescribed cellular differentiation patterns. These complex dynamics can take the form of chaotic, stochastic, or noisy chaotic dynamics. Based on this outcome and previous research, it is established that a generic open chemical reactor can generate an exceptionally large number of different cellular patterns. The mechanism of pattern generation is robust under perturbations and it is based on a combination of Turing’s machines, Turing instability and L. Wolpert’s gradients. These results can help us to explain the formidable adaptive capacities of biochemical systems. Nature Publishing Group UK 2023-05-09 /pmc/articles/PMC10170119/ /pubmed/37160971 http://dx.doi.org/10.1038/s41598-023-34041-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Reinitz, J.
Vakulenko, S.
Sudakow, I.
Grigoriev, D.
Robust morphogenesis by chaotic dynamics
title Robust morphogenesis by chaotic dynamics
title_full Robust morphogenesis by chaotic dynamics
title_fullStr Robust morphogenesis by chaotic dynamics
title_full_unstemmed Robust morphogenesis by chaotic dynamics
title_short Robust morphogenesis by chaotic dynamics
title_sort robust morphogenesis by chaotic dynamics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10170119/
https://www.ncbi.nlm.nih.gov/pubmed/37160971
http://dx.doi.org/10.1038/s41598-023-34041-x
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