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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 Manar 2092, Tunis, Tunisia, LAMSADE CNRS UMR 7243, Paris Dauphine University, PSL Research University, Place du Maréchal de Lattre deTassigny, Paris, France ; 2 LIPAH, Faculté des Sciences de Tunis, Université de Tunis El Manar 2092, Tunis, Tunisia, Institut Supérieur d'Informatique, Université de Tunis El Manar, 1002, Tunis, Tunisia ; 3 LAMSADE CNRS UMR 7243, Paris Dauphine University, PSL Research University, Place du Maréchal de Lattre deTassigny, Paris, France

ISBN: 978-989-758-443-5

Keyword(s): Community Detection, Biological Networks, PPI Networks, Genetic Algorithm, Heuristic Crossover.

Abstract: Community 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. Exp erimental results show the ability of our Genetic Algorithm to detect communities of genes that are semantically similar or/and interacting. (More)

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Paper citation in several formats:
BEN M'BAREK, M.; Borgi, A.; Ben Hmida, S. and Rukoz, M. (2020). Generic GA-PPI-Net: Generic Evolutionary Algorithm to Detect Semantic and Topological Biological Communities.In Proceedings of the 15th International Conference on Software Technologies - Volume 1: ICSOFT, ISBN 978-989-758-443-5, pages 295-306. DOI: 10.5220/0009779902950306

@conference{icsoft20,
author={BEN M'BAREK, M. and Amel Borgi. and Sana Ben Hmida. and Marta Rukoz.},
title={Generic GA-PPI-Net: Generic Evolutionary Algorithm to Detect Semantic and Topological Biological Communities},
booktitle={Proceedings of the 15th International Conference on Software Technologies - Volume 1: ICSOFT,},
year={2020},
pages={295-306},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009779902950306},
isbn={978-989-758-443-5},
}

TY - CONF

JO - Proceedings of the 15th International Conference on Software Technologies - Volume 1: ICSOFT,
TI - Generic GA-PPI-Net: Generic Evolutionary Algorithm to Detect Semantic and Topological Biological Communities
SN - 978-989-758-443-5
AU - BEN M'BAREK, M.
AU - Borgi, A.
AU - Ben Hmida, S.
AU - Rukoz, M.
PY - 2020
SP - 295
EP - 306
DO - 10.5220/0009779902950306

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