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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, Marwa
hal.structure.identifierLaboratoire d'Informatique, Programmation, Algorithmique et Heuristique [LIPAH]
dc.contributor.authorBorgi, Amel
hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorBen Hmida, Sana
hal.structure.identifierLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
dc.contributor.authorRukoz, Marta
dc.date.accessioned2020-10-20T10:40:50Z
dc.date.available2020-10-20T10:40:50Z
dc.date.issued2020
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/21129
dc.language.isoenen
dc.subjectCommunity detectionen
dc.subjectGenetic algorithm Protein-Protein or gene-gene interaction networksen
dc.subjectSemantic Similarityen
dc.subjectGene Ontologyen
dc.subject.ddc005en
dc.titleGA-PPI-Net: A Genetic Algorithm for Community Detection in Protein-Protein Interaction Networksen
dc.typeCommunication / Conférence
dc.description.abstractenCommunity detection has become an important research direction for data mining in complex networks. It aims to identify topological structures and discover patterns in complex networks, which presents an important problem of great significance. In this paper, we are interested in the detection of communities in the Protein-Protein or Gene-gene Interaction (PPI) networks. These networks represent a set of proteins or genes that collaborate at the same cellular function. The goal is to identify such semantic and topological communities from gene annotation sources such as Gene Ontology. We propose a Genetic Algorithm (GA) based approach to detect communities having different sizes from PPI networks. For this purpose, we introduce three specific components to the GA: a fitness function based on a similarity measure and the interaction value between proteins or genes, a solution for representing a community with dynamic size and a specific mutation operator. In the computational tests carried out in this work, the introduced algorithm achieved excellent results to detect existing or even new communities from PPI networks.en
dc.identifier.citationpages133-155en
dc.relation.ispartoftitleSoftware Technologiesen
dc.relation.ispartofeditorvan Sinderen, Marten
dc.relation.ispartofeditorMaciaszek, Leszek A.
dc.relation.ispartofpublnameSpringer International Publishingen
dc.relation.ispartofpublcityBerlin Heidelbergen
dc.relation.ispartofpages229en
dc.relation.ispartofurl10.1007/978-3-030-52991-8en
dc.subject.ddclabelProgrammation, logiciels, organisation des donnéesen
dc.relation.ispartofisbn978-3-030-52990-1; 978-3-030-52991-8en
dc.relation.conftitle14th International Conference, ICSOFT 2019 (Revised Selected Papers)en
dc.relation.confdate2020-07
dc.relation.confcityPragueen
dc.relation.confcountryCzech Republicen
dc.relation.forthcomingnonen
dc.identifier.doi10.1007/978-3-030-52991-8_7en
dc.description.ssrncandidatenonen
dc.description.halcandidateouien
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewednonen
dc.relation.Isversionofjnlpeerreviewednonen
dc.date.updated2020-10-20T10:35:14Z
hal.identifierhal-02972333*
hal.version1*
hal.author.functionaut
hal.author.functionaut
hal.author.functionaut
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