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Linked Open Data
A semi-parametric statistical test to compare complex networks
Identificadores del recurso
FUJITA, A.; LIRA, E. S.; SANTOS, S. S.; BANDO, S. Y.; SOARES, G. E.; TAKAHASHI, D. Y. A semi-parametric statistical test to compare complex networks. Journal of Complex Networks, [s. l.], p. 1-17, ago. 2019. DOI: https://doi.org/10.1093/comnet/cnz028. Disponível em: https://academic.oup.com/comnet/advance-article-abstract/doi/10.1093/comnet/cnz028/5543003?redirectedFrom=fulltext. Acesso em: 04 set. 2019.
https://repositorio.ufrn.br/jspui/handle/123456789/27629
https://doi.org/10.1093/comnet/cnz028
Procedencia
(LA Referencia)

Ficha

Título:
A semi-parametric statistical test to compare complex networks
Tema:
Random graph
parameter estimation
model selection
ANOVA
graph spectrum
isomorphism
Descripción:
The modelling of real-world data as complex networks is ubiquitous in several scientific fields, for example, in molecular biology, we study gene regulatory networks and protein–protein interaction (PPI)_networks; in neuroscience, we study functional brain networks; and in social science, we analyse social networks. In contrast to theoretical graphs, real-world networks are better modelled as realizations of a random process. Therefore, analyses using methods based on deterministic graphs may be inappropriate. For example, verifying the isomorphism between two graphs is of limited use to decide whether two (or more) real-world networks are generated from the same random process. To overcome this problem, in this article, we introduce a semi-parametric approach similar to the analysis of variance to test the equality of generative models of two or more complex networks. We measure the performance of the proposed statistic using Monte Carlo simulations and illustrate its usefulness by comparing PPI networks of six enteric pathogens.
Fuente:
reponame:Repositório Institucional da UFRN
instname:Universidade Federal do Rio Grande do Norte
instacron:UFRN
Idioma:
English
Autor/Productor:
Fujita, Andre
Lira, Eduardo Silva
Santos, Suzana de Siqueira
Bando, Silvia Yumi
Soares, Gabriela Eleuterio
Takahashi, Daniel Yasumasa
Derechos:
info:eu-repo/semantics/openAccess
Fecha:
2019-09-04T14:16:47Z
2019-08-02
Tipo de recurso:
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
About:
http://repositorio.ufrn.br/oai/oai:repositorio.ufrn.br:123456789/276292019-09-08 02:16:45.907http://www.openarchives.org/OAI/2.0/oai_dc/Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte

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