GA-PPI-Net: A Genetic Algorithm for Community Detection in Protein-Protein Interaction Networks - LAMSADE (Laboratoire d'Analyse et de Modélisation des Systèmes pour l'Aide à la Décision) Accéder directement au contenu
Communication Dans Un Congrès Année : 2020

GA-PPI-Net: A Genetic Algorithm for Community Detection in Protein-Protein Interaction Networks

Résumé

Community 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.
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Dates et versions

hal-02972333 , version 1 (20-10-2020)

Identifiants

Citer

Marwa Ben M’barek, Amel Borgi, Sana Ben Hmida, Marta Rukoz. GA-PPI-Net: A Genetic Algorithm for Community Detection in Protein-Protein Interaction Networks. 14th International Conference, ICSOFT 2019 (Revised Selected Papers), Jul 2019, Prague, Czech Republic. pp.133-155, ⟨10.1007/978-3-030-52991-8_7⟩. ⟨hal-02972333⟩
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