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Center of mass in complex networks

Network dynamics is always a big challenge in nonlinear dynamics. Although great advancements have been made in various types of complex systems, an universal theoretical framework is required. In this paper, we introduce the concept of center of ‘mass’ of complex networks, where ‘mass’ stands for n...

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Autores principales: Fu, Chuanji, Gao, Yachun, Cai, Shimin, Yang, Hongchun, Yang, Chun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5247737/
https://www.ncbi.nlm.nih.gov/pubmed/28106109
http://dx.doi.org/10.1038/srep40982
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author Fu, Chuanji
Gao, Yachun
Cai, Shimin
Yang, Hongchun
Yang, Chun
author_facet Fu, Chuanji
Gao, Yachun
Cai, Shimin
Yang, Hongchun
Yang, Chun
author_sort Fu, Chuanji
collection PubMed
description Network dynamics is always a big challenge in nonlinear dynamics. Although great advancements have been made in various types of complex systems, an universal theoretical framework is required. In this paper, we introduce the concept of center of ‘mass’ of complex networks, where ‘mass’ stands for node importance or centrality in contrast to that of particle systems, and further prove that the phase transition and evolutionary state of the system can be characterized by the activity of center of ‘mass’. The steady states of several complex networks (gene regulatory networks and epidemic spreading systems) are then studied by analytically calculating the decoupled equation of the dynamic activity of center of ‘mass’, which is derived from the dynamic equation of the complex networks. The limitations of this method are also pointed out, such as the dynamical problems that related with the relative activities among components, and those systems that consist of oscillatory or chaotic motions.
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spelling pubmed-52477372017-01-23 Center of mass in complex networks Fu, Chuanji Gao, Yachun Cai, Shimin Yang, Hongchun Yang, Chun Sci Rep Article Network dynamics is always a big challenge in nonlinear dynamics. Although great advancements have been made in various types of complex systems, an universal theoretical framework is required. In this paper, we introduce the concept of center of ‘mass’ of complex networks, where ‘mass’ stands for node importance or centrality in contrast to that of particle systems, and further prove that the phase transition and evolutionary state of the system can be characterized by the activity of center of ‘mass’. The steady states of several complex networks (gene regulatory networks and epidemic spreading systems) are then studied by analytically calculating the decoupled equation of the dynamic activity of center of ‘mass’, which is derived from the dynamic equation of the complex networks. The limitations of this method are also pointed out, such as the dynamical problems that related with the relative activities among components, and those systems that consist of oscillatory or chaotic motions. Nature Publishing Group 2017-01-20 /pmc/articles/PMC5247737/ /pubmed/28106109 http://dx.doi.org/10.1038/srep40982 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Fu, Chuanji
Gao, Yachun
Cai, Shimin
Yang, Hongchun
Yang, Chun
Center of mass in complex networks
title Center of mass in complex networks
title_full Center of mass in complex networks
title_fullStr Center of mass in complex networks
title_full_unstemmed Center of mass in complex networks
title_short Center of mass in complex networks
title_sort center of mass in complex networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5247737/
https://www.ncbi.nlm.nih.gov/pubmed/28106109
http://dx.doi.org/10.1038/srep40982
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