Macro- and mesoscale pattern interdependencies in complex networks

Identifying and explaining the structure of complex networks at different scales has become an important problem across disciplines. At the mesoscale, modular architecture has attracted most of the attention. At the macroscale, other arrangements-e.g. nestedness or core-periphery-have been studied i...

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Autores: Palazzi Nieves, Maria José, Borge-Holthoefer, Javier, Tessone, Claudio J., Solé-Ribalta, Albert
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2019
País:España
Institución:Universitat Oberta de Catalunya (UOC)
Repositorio:O2, repositorio institucional de la UOC
OAI Identifier:oai:openaccess.uoc.edu:10609/124286
Acceso en línea:http://hdl.handle.net/10609/124286
Access Level:acceso abierto
Palabra clave:complex networks
mesoscale
nestedness
modularity
ecological networks
xarxes ecològiques
xarxes complexes
mesoscala
modularitat
anidament
redes complejas
mesoescala
modularidad
anidamiento
redes ecológicas
Algorithms
Algorismes
Algoritmos
id ES_b6ba3b4d375e77b4dba80b7ad2a4e7b6
oai_identifier_str oai:openaccess.uoc.edu:10609/124286
network_acronym_str ES
network_name_str España
repository_id_str
spelling Macro- and mesoscale pattern interdependencies in complex networksPalazzi Nieves, Maria JoséBorge-Holthoefer, JavierTessone, Claudio J.Solé-Ribalta, Albertcomplex networksmesoscalenestednessmodularityecological networksxarxes ecològiquesxarxes complexesmesoscalamodularitatanidamentredes complejasmesoescalamodularidadanidamientoredes ecológicasAlgorithmsAlgorismesAlgoritmosIdentifying and explaining the structure of complex networks at different scales has become an important problem across disciplines. At the mesoscale, modular architecture has attracted most of the attention. At the macroscale, other arrangements-e.g. nestedness or core-periphery-have been studied in parallel, but to a much lesser extent. However, empirical evidence increasingly suggests that characterizing a network with a unique pattern typology may be too simplistic, since a system can integrate properties from distinct organizations at different scales. Here, we explore the relationship between some of these different organizational patterns: two at the mesoscale (modularity and in-block nestedness); and one at the macroscale (nestedness). We show experimentally and analytically that nestedness imposes bounds to modularity, with exact analytical results in idealized scenarios. Specifically, we show that nestedness and modularity are interdependent. Furthermore, we analytically evidence that in-block nestedness provides a natural combination between nested and modular networks, taking structural properties of both. Far from a mere theoretical exercise, understanding the boundaries that discriminate each architecture is fundamental, to the extent that modularity and nestedness are known to place heavy dynamical effects on processes, such as species abundances and stability in ecology.Journal of the Royal Society InterfaceUniversitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)Universität Zürich202020202019info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10609/124286reponame:O2, repositorio institucional de la UOCinstname:Universitat Oberta de Catalunya (UOC)InglésJournal of the Royal Society Interface, 2019, 16(159)https://doi.org/10.1098/rsif.2019.0553info:eu-repo/grantAgreement/PGC2018-096999-A-I00//CC BYhttp://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccessoai:openaccess.uoc.edu:10609/1242862026-05-28T12:42:01Z
dc.title.none.fl_str_mv Macro- and mesoscale pattern interdependencies in complex networks
title Macro- and mesoscale pattern interdependencies in complex networks
spellingShingle Macro- and mesoscale pattern interdependencies in complex networks
Palazzi Nieves, Maria José
complex networks
mesoscale
nestedness
modularity
ecological networks
xarxes ecològiques
xarxes complexes
mesoscala
modularitat
anidament
redes complejas
mesoescala
modularidad
anidamiento
redes ecológicas
Algorithms
Algorismes
Algoritmos
title_short Macro- and mesoscale pattern interdependencies in complex networks
title_full Macro- and mesoscale pattern interdependencies in complex networks
title_fullStr Macro- and mesoscale pattern interdependencies in complex networks
title_full_unstemmed Macro- and mesoscale pattern interdependencies in complex networks
title_sort Macro- and mesoscale pattern interdependencies in complex networks
dc.creator.none.fl_str_mv Palazzi Nieves, Maria José
Borge-Holthoefer, Javier
Tessone, Claudio J.
Solé-Ribalta, Albert
author Palazzi Nieves, Maria José
author_facet Palazzi Nieves, Maria José
Borge-Holthoefer, Javier
Tessone, Claudio J.
Solé-Ribalta, Albert
author_role author
author2 Borge-Holthoefer, Javier
Tessone, Claudio J.
Solé-Ribalta, Albert
author2_role author
author
author
dc.contributor.none.fl_str_mv Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)
Universität Zürich
dc.subject.none.fl_str_mv complex networks
mesoscale
nestedness
modularity
ecological networks
xarxes ecològiques
xarxes complexes
mesoscala
modularitat
anidament
redes complejas
mesoescala
modularidad
anidamiento
redes ecológicas
Algorithms
Algorismes
Algoritmos
topic complex networks
mesoscale
nestedness
modularity
ecological networks
xarxes ecològiques
xarxes complexes
mesoscala
modularitat
anidament
redes complejas
mesoescala
modularidad
anidamiento
redes ecológicas
Algorithms
Algorismes
Algoritmos
description Identifying and explaining the structure of complex networks at different scales has become an important problem across disciplines. At the mesoscale, modular architecture has attracted most of the attention. At the macroscale, other arrangements-e.g. nestedness or core-periphery-have been studied in parallel, but to a much lesser extent. However, empirical evidence increasingly suggests that characterizing a network with a unique pattern typology may be too simplistic, since a system can integrate properties from distinct organizations at different scales. Here, we explore the relationship between some of these different organizational patterns: two at the mesoscale (modularity and in-block nestedness); and one at the macroscale (nestedness). We show experimentally and analytically that nestedness imposes bounds to modularity, with exact analytical results in idealized scenarios. Specifically, we show that nestedness and modularity are interdependent. Furthermore, we analytically evidence that in-block nestedness provides a natural combination between nested and modular networks, taking structural properties of both. Far from a mere theoretical exercise, understanding the boundaries that discriminate each architecture is fundamental, to the extent that modularity and nestedness are known to place heavy dynamical effects on processes, such as species abundances and stability in ecology.
publishDate 2019
dc.date.none.fl_str_mv 2019
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10609/124286
url http://hdl.handle.net/10609/124286
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Journal of the Royal Society Interface, 2019, 16(159)
https://doi.org/10.1098/rsif.2019.0553
info:eu-repo/grantAgreement/PGC2018-096999-A-I00//
dc.rights.none.fl_str_mv CC BY
http://creativecommons.org/licenses/by/3.0/es/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv CC BY
http://creativecommons.org/licenses/by/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Journal of the Royal Society Interface
publisher.none.fl_str_mv Journal of the Royal Society Interface
dc.source.none.fl_str_mv reponame:O2, repositorio institucional de la UOC
instname:Universitat Oberta de Catalunya (UOC)
instname_str Universitat Oberta de Catalunya (UOC)
reponame_str O2, repositorio institucional de la UOC
collection O2, repositorio institucional de la UOC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869417470976065536
score 15.300719

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