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hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorBen M’Barek, M.
hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorHmida, Hmida
dc.contributor.authorBorgi, Amel
hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorRukoz, Marta
dc.date.accessioned2022-03-01T10:48:29Z
dc.date.available2022-03-01T10:48:29Z
dc.date.issued2021
dc.identifier.issn1877-0509
dc.identifier.urihttps://basepub.dauphine.psl.eu/handle/123456789/22847
dc.description25th International Conference KES-2021, Sep 2021, Szczecin, Polanden
dc.language.isoenen
dc.subjectCommunity detectionen
dc.subjectGenetic Algorithmen
dc.subjectClusteringen
dc.subjectProtein-protein interaction networksen
dc.subjectSemantic Similarityen
dc.subject.ddc006.3en
dc.titleGA-PPI-Net Approach vs Analytical Approaches for Community Detection in PPI Networksen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenCommunity detection has become an important research direction for data mining in complex networks. It aims to identify topo-logical structures and discover patterns in complex networks, which presents an important problem of great significance. Prediction of communities from Protein-Protein Interaction (PPI) networks is important problem in system biology as they control different cellular functions. These networks represent a set of proteins that collaborate at the same cellular function. With the increment of genome-scale protein–protein interaction data for different species, various computational methods focus on identifying protein community from PPI networks. In this paper, we are interested in evaluating the proposed genetic algorithm GA-PPI-Net and three clustering methods for community detection. In the computational tests carried out in this work, the proposed genetic algorithm achieved excellent results to detect existing or even new communities from PPI networks.en
dc.relation.isversionofjnlnameProcedia Computer Science
dc.relation.isversionofjnlvol192en
dc.relation.isversionofjnldate2021
dc.relation.isversionofjnlpages903-912en
dc.relation.isversionofdoi10.1016/j.procs.2021.08.093en
dc.relation.isversionofjnlpublisherElsevieren
dc.subject.ddclabelIntelligence artificielleen
dc.relation.forthcomingnonen
dc.description.ssrncandidatenon
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewednonen
dc.date.updated2022-03-01T10:46:54Z
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