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Assessing diversity in multiplex networks
Diversity, understood as the variety of different elements or configurations that an extensive system has, is a crucial property that allows maintaining the system’s functionality in a changing environment, where failures, random events or malicious attacks are often unavoidable. Despite the relevan...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6418208/ https://www.ncbi.nlm.nih.gov/pubmed/30872604 http://dx.doi.org/10.1038/s41598-019-38869-0 |
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author | Carpi, Laura C. Schieber, Tiago A. Pardalos, Panos M. Marfany, Gemma Masoller, Cristina Díaz-Guilera, Albert Ravetti, Martín G. |
author_facet | Carpi, Laura C. Schieber, Tiago A. Pardalos, Panos M. Marfany, Gemma Masoller, Cristina Díaz-Guilera, Albert Ravetti, Martín G. |
author_sort | Carpi, Laura C. |
collection | PubMed |
description | Diversity, understood as the variety of different elements or configurations that an extensive system has, is a crucial property that allows maintaining the system’s functionality in a changing environment, where failures, random events or malicious attacks are often unavoidable. Despite the relevance of preserving diversity in the context of ecology, biology, transport, finances, etc., the elements or configurations that more contribute to the diversity are often unknown, and thus, they can not be protected against failures or environmental crises. This is due to the fact that there is no generic framework that allows identifying which elements or configurations have crucial roles in preserving the diversity of the system. Existing methods treat the level of heterogeneity of a system as a measure of its diversity, being unsuitable when systems are composed of a large number of elements with different attributes and types of interactions. Besides, with limited resources, one needs to find the best preservation policy, i.e., one needs to solve an optimization problem. Here we aim to bridge this gap by developing a metric between labeled graphs to compute the diversity of the system, which allows identifying the most relevant components, based on their contribution to a global diversity value. The proposed framework is suitable for large multiplex structures, which are constituted by a set of elements represented as nodes, which have different types of interactions, represented as layers. The proposed method allows us to find, in a genetic network (HIV-1), the elements with the highest diversity values, while in a European airline network, we systematically identify the companies that maximize (and those that less compromise) the variety of options for routes connecting different airports. |
format | Online Article Text |
id | pubmed-6418208 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-64182082019-03-18 Assessing diversity in multiplex networks Carpi, Laura C. Schieber, Tiago A. Pardalos, Panos M. Marfany, Gemma Masoller, Cristina Díaz-Guilera, Albert Ravetti, Martín G. Sci Rep Article Diversity, understood as the variety of different elements or configurations that an extensive system has, is a crucial property that allows maintaining the system’s functionality in a changing environment, where failures, random events or malicious attacks are often unavoidable. Despite the relevance of preserving diversity in the context of ecology, biology, transport, finances, etc., the elements or configurations that more contribute to the diversity are often unknown, and thus, they can not be protected against failures or environmental crises. This is due to the fact that there is no generic framework that allows identifying which elements or configurations have crucial roles in preserving the diversity of the system. Existing methods treat the level of heterogeneity of a system as a measure of its diversity, being unsuitable when systems are composed of a large number of elements with different attributes and types of interactions. Besides, with limited resources, one needs to find the best preservation policy, i.e., one needs to solve an optimization problem. Here we aim to bridge this gap by developing a metric between labeled graphs to compute the diversity of the system, which allows identifying the most relevant components, based on their contribution to a global diversity value. The proposed framework is suitable for large multiplex structures, which are constituted by a set of elements represented as nodes, which have different types of interactions, represented as layers. The proposed method allows us to find, in a genetic network (HIV-1), the elements with the highest diversity values, while in a European airline network, we systematically identify the companies that maximize (and those that less compromise) the variety of options for routes connecting different airports. Nature Publishing Group UK 2019-03-14 /pmc/articles/PMC6418208/ /pubmed/30872604 http://dx.doi.org/10.1038/s41598-019-38869-0 Text en © The Author(s) 2019 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Carpi, Laura C. Schieber, Tiago A. Pardalos, Panos M. Marfany, Gemma Masoller, Cristina Díaz-Guilera, Albert Ravetti, Martín G. Assessing diversity in multiplex networks |
title | Assessing diversity in multiplex networks |
title_full | Assessing diversity in multiplex networks |
title_fullStr | Assessing diversity in multiplex networks |
title_full_unstemmed | Assessing diversity in multiplex networks |
title_short | Assessing diversity in multiplex networks |
title_sort | assessing diversity in multiplex networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6418208/ https://www.ncbi.nlm.nih.gov/pubmed/30872604 http://dx.doi.org/10.1038/s41598-019-38869-0 |
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