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LAMSADE CNRS UMR 7243, Paris Dauphine University, PSL Research University, Place du Maréchal de Lattre de Tassigny, Paris and France

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1 Papers

Genetic Algorithm to Detect Different Sizes’ Communities from Protein-Protein Interaction Networks

Topic: Artificial Intelligence Applications

Authors: Marwa Ben M’Barek ¹ , Amel Borgi ² , Sana Ben Hmida ³ and Marta Rukoz ³

Affiliations: ¹ LIPAH, Faculté des Sciences de Tunis, Université de Tunis El Manar2092, Tunis, Tunisia, LAMSADE CNRS UMR 7243, Paris Dauphine University, PSL Research University, Place du Maréchal de Lattre de Tassigny, Paris and France , ² LIPAH, Faculté des Sciences de Tunis, Université de Tunis El Manar2092, Tunis, Tunisia, Institut Supérieur d'Informatique, Université de Tunis El Manar, 1002, Tunis and Tunisia , ³ LAMSADE CNRS UMR 7243, Paris Dauphine University, PSL Research University, Place du Maréchal de Lattre de Tassigny, Paris and France

Digital Object Identifier: 10.5220/0007836703590370

Proceedings of ICSOFT 2019, ISBN: 978-989-758-379-7

Quick Abstract

The community detection in large networks is an important problem in many scientific fields ranging from Biology to Sociology and Computer Science. In this paper, we are interested in the detection of communities in the Protein-protein or Gene-gene Interaction (PPI) 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 communities from gene annotation sources such as Gene Ontology. We propose a Genetic Algorithm based approach to detect communities having different sizes from PPI networks. For this purpose, we use a fitness function based on a similarity measure and the interaction value between proteins or genes. Moreover, a specific solution for representing a community and a specific mutation operator are introduced. In the computational tests carried out in this work, the introduced algorithm achieved excellent results to detect existing or even new communities from Protein-protein or Gene-gene Interaction networks.