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Chaotic Motifs in Gene Regulatory Networks

Chaos should occur often in gene regulatory networks (GRNs) which have been widely described by nonlinear coupled ordinary differential equations, if their dimensions are no less than 3. It is therefore puzzling that chaos has never been reported in GRNs in nature and is also extremely rare in model...

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Autores principales: Zhang, Zhaoyang, Ye, Weiming, Qian, Yu, Zheng, Zhigang, Huang, Xuhui, Hu, Gang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3391214/
https://www.ncbi.nlm.nih.gov/pubmed/22792171
http://dx.doi.org/10.1371/journal.pone.0039355
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author Zhang, Zhaoyang
Ye, Weiming
Qian, Yu
Zheng, Zhigang
Huang, Xuhui
Hu, Gang
author_facet Zhang, Zhaoyang
Ye, Weiming
Qian, Yu
Zheng, Zhigang
Huang, Xuhui
Hu, Gang
author_sort Zhang, Zhaoyang
collection PubMed
description Chaos should occur often in gene regulatory networks (GRNs) which have been widely described by nonlinear coupled ordinary differential equations, if their dimensions are no less than 3. It is therefore puzzling that chaos has never been reported in GRNs in nature and is also extremely rare in models of GRNs. On the other hand, the topic of motifs has attracted great attention in studying biological networks, and network motifs are suggested to be elementary building blocks that carry out some key functions in the network. In this paper, chaotic motifs (subnetworks with chaos) in GRNs are systematically investigated. The conclusion is that: (i) chaos can only appear through competitions between different oscillatory modes with rivaling intensities. Conditions required for chaotic GRNs are found to be very strict, which make chaotic GRNs extremely rare. (ii) Chaotic motifs are explored as the simplest few-node structures capable of producing chaos, and serve as the intrinsic source of chaos of random few-node GRNs. Several optimal motifs causing chaos with atypically high probability are figured out. (iii) Moreover, we discovered that a number of special oscillators can never produce chaos. These structures bring some advantages on rhythmic functions and may help us understand the robustness of diverse biological rhythms. (iv) The methods of dominant phase-advanced driving (DPAD) and DPAD time fraction are proposed to quantitatively identify chaotic motifs and to explain the origin of chaotic behaviors in GRNs.
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spelling pubmed-33912142012-07-12 Chaotic Motifs in Gene Regulatory Networks Zhang, Zhaoyang Ye, Weiming Qian, Yu Zheng, Zhigang Huang, Xuhui Hu, Gang PLoS One Research Article Chaos should occur often in gene regulatory networks (GRNs) which have been widely described by nonlinear coupled ordinary differential equations, if their dimensions are no less than 3. It is therefore puzzling that chaos has never been reported in GRNs in nature and is also extremely rare in models of GRNs. On the other hand, the topic of motifs has attracted great attention in studying biological networks, and network motifs are suggested to be elementary building blocks that carry out some key functions in the network. In this paper, chaotic motifs (subnetworks with chaos) in GRNs are systematically investigated. The conclusion is that: (i) chaos can only appear through competitions between different oscillatory modes with rivaling intensities. Conditions required for chaotic GRNs are found to be very strict, which make chaotic GRNs extremely rare. (ii) Chaotic motifs are explored as the simplest few-node structures capable of producing chaos, and serve as the intrinsic source of chaos of random few-node GRNs. Several optimal motifs causing chaos with atypically high probability are figured out. (iii) Moreover, we discovered that a number of special oscillators can never produce chaos. These structures bring some advantages on rhythmic functions and may help us understand the robustness of diverse biological rhythms. (iv) The methods of dominant phase-advanced driving (DPAD) and DPAD time fraction are proposed to quantitatively identify chaotic motifs and to explain the origin of chaotic behaviors in GRNs. Public Library of Science 2012-07-06 /pmc/articles/PMC3391214/ /pubmed/22792171 http://dx.doi.org/10.1371/journal.pone.0039355 Text en Zhang et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Zhang, Zhaoyang
Ye, Weiming
Qian, Yu
Zheng, Zhigang
Huang, Xuhui
Hu, Gang
Chaotic Motifs in Gene Regulatory Networks
title Chaotic Motifs in Gene Regulatory Networks
title_full Chaotic Motifs in Gene Regulatory Networks
title_fullStr Chaotic Motifs in Gene Regulatory Networks
title_full_unstemmed Chaotic Motifs in Gene Regulatory Networks
title_short Chaotic Motifs in Gene Regulatory Networks
title_sort chaotic motifs in gene regulatory networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3391214/
https://www.ncbi.nlm.nih.gov/pubmed/22792171
http://dx.doi.org/10.1371/journal.pone.0039355
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