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Multiscale Information Propagation in Emergent Functional Networks

Complex biological systems consist of large numbers of interconnected units, characterized by emergent properties such as collective computation. In spite of all the progress in the last decade, we still lack a deep understanding of how these properties arise from the coupling between the structure...

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Detalles Bibliográficos
Autores principales: Ghavasieh, Arsham, De Domenico, Manlio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534377/
https://www.ncbi.nlm.nih.gov/pubmed/34682093
http://dx.doi.org/10.3390/e23101369
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author Ghavasieh, Arsham
De Domenico, Manlio
author_facet Ghavasieh, Arsham
De Domenico, Manlio
author_sort Ghavasieh, Arsham
collection PubMed
description Complex biological systems consist of large numbers of interconnected units, characterized by emergent properties such as collective computation. In spite of all the progress in the last decade, we still lack a deep understanding of how these properties arise from the coupling between the structure and dynamics. Here, we introduce the multiscale emergent functional state, which can be represented as a network where links encode the flow exchange between the nodes, calculated using diffusion processes on top of the network. We analyze the emergent functional state to study the distribution of the flow among components of 92 fungal networks, identifying their functional modules at different scales and, more importantly, demonstrating the importance of functional modules for the information content of networks, quantified in terms of network spectral entropy. Our results suggest that the topological complexity of fungal networks guarantees the existence of functional modules at different scales keeping the information entropy, and functional diversity, high.
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spelling pubmed-85343772021-10-23 Multiscale Information Propagation in Emergent Functional Networks Ghavasieh, Arsham De Domenico, Manlio Entropy (Basel) Article Complex biological systems consist of large numbers of interconnected units, characterized by emergent properties such as collective computation. In spite of all the progress in the last decade, we still lack a deep understanding of how these properties arise from the coupling between the structure and dynamics. Here, we introduce the multiscale emergent functional state, which can be represented as a network where links encode the flow exchange between the nodes, calculated using diffusion processes on top of the network. We analyze the emergent functional state to study the distribution of the flow among components of 92 fungal networks, identifying their functional modules at different scales and, more importantly, demonstrating the importance of functional modules for the information content of networks, quantified in terms of network spectral entropy. Our results suggest that the topological complexity of fungal networks guarantees the existence of functional modules at different scales keeping the information entropy, and functional diversity, high. MDPI 2021-10-19 /pmc/articles/PMC8534377/ /pubmed/34682093 http://dx.doi.org/10.3390/e23101369 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Ghavasieh, Arsham
De Domenico, Manlio
Multiscale Information Propagation in Emergent Functional Networks
title Multiscale Information Propagation in Emergent Functional Networks
title_full Multiscale Information Propagation in Emergent Functional Networks
title_fullStr Multiscale Information Propagation in Emergent Functional Networks
title_full_unstemmed Multiscale Information Propagation in Emergent Functional Networks
title_short Multiscale Information Propagation in Emergent Functional Networks
title_sort multiscale information propagation in emergent functional networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8534377/
https://www.ncbi.nlm.nih.gov/pubmed/34682093
http://dx.doi.org/10.3390/e23101369
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