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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.accessioned2020-10-20T14:51:03Z
dc.date.available2020-10-20T14:51:03Z
dc.date.issued2020
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/21130
dc.descriptionCette conférence a été exceptionnellement organisée en distanciel sur le web en raison de la pandémie COVID-19.en
dc.language.isoenen
dc.subjectCommunity Detectionen
dc.subjectBiological Networksen
dc.subjectPPI Networksen
dc.subjectGenetic Algorithmen
dc.subjectHeuristic Crossoveren
dc.subject.ddc005en
dc.titleGeneric GA-PPI-Net: Generic Evolutionary Algorithm to Detect Semantic and Topological Biological Communitiesen
dc.typeCommunication / Conférence
dc.description.abstractenCommunity detection aims to identify topological structures and discover patterns in complex networks. It presents an important problem of great significance in many fields. In this paper, we are interested in the detection of communities in biological networks. These networks represent protein-protein or gene-gene interactions which corresponds to a set of proteins or genes that collaborate at the same cellular function. The goal is to identify such semantic and/or topological communities from gene annotation sources such as Gene Ontology. We propose a Genetic Algorithm (GA) based technique as a clustering approach to detect communities from biological networks. For this purpose, we introduce four 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, an heuristic crossover to strengthen links in the communities and a specific mutation operator. Experimental results show the ability of our Genetic Algorithm to detect communities of genes that are semantically similar or/and interacting.en
dc.identifier.citationpages295-306en
dc.relation.ispartoftitleProceedings of the 15th International Conference on Software Technologiesen
dc.relation.ispartofeditorvan Sinderen, Marten
dc.relation.ispartofeditorFill, Hans-Georg
dc.relation.ispartofeditorMaciaszek, Leszek
dc.relation.ispartofpublnameSciTe Pressen
dc.subject.ddclabelProgrammation, logiciels, organisation des donnéesen
dc.relation.ispartofisbn978-989-758-443-5en
dc.relation.conftitle15th International Conference on Software Technologies (ICSOFT 2020)en
dc.relation.confdate2020-07
dc.relation.forthcomingnonen
dc.identifier.doi10.5220/0009779902950306en
dc.description.ssrncandidatenonen
dc.description.halcandidateouien
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewednonen
dc.relation.Isversionofjnlpeerreviewednonen
dc.date.updated2020-10-20T10:54:50Z
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