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

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ICSOFT_2019_25.pdf (760.3Kb)
Date
2019
Dewey
Programmation, logiciels, organisation des données
Sujet
Community Detection; Genetic Algorithm; Semantic Similarity; Protein-Protein or Gene-Gene Interaction Networks; Gene Ontology.
DOI
http://dx.doi.org/10.5220/0007836703590370
Conference name
Proceedings of the 14th International Conference on Software Technologie
Conference date
2019
Author
M. van Sinderen, L. Maciaszek
Publisher
SciTe Press
ISBN
978-989-758-379-7
URI
https://basepub.dauphine.fr/handle/123456789/20037
Collections
  • LAMSADE : Publications
Metadata
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Author
Ben M'barek, Marwa
Borgi, Amel
Ben Hamida, Sana
Rukoz, Marta
Type
Communication / Conférence
Item number of pages
359-370
Abstract (EN)
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 cellularfunction. The goal is to identify such communities from gene annotation sources such as Gene Ontology. Wepropose 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.

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