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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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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. |
format | Online Article Text |
id | pubmed-3391214 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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