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

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Software Technologies (ICSOFT 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1250))

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Abstract

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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Notes

  1. 1.

    The degree of a node is the number of edges incident to the node.

  2. 2.

    https://pythonhosted.org/inspyred/.

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Acknowledgements

We would like to show our gratitude to Dr. Walid BEDHIAFI (Laboratoire de Génétique Immunologie et Pathologies Humaines, Université de Tunis El Manar) for assistance to comprehend the biological fields and for the interpretation of the results.

Author information

Authors and Affiliations

  1. LIPAH, Faculté des Sciences de Tunis, Université de Tunis El Manar, 2092, Tunis, Tunisia

    Marwa Ben M’barek & Amel Borgi

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

    Marwa Ben M’barek, Sana Ben Hmida & Marta Rukoz

  3. Institut Supérieur d’Informatique, Université de Tunis El Manar, 1002, Tunis, Tunisia

    Amel Borgi

Authors
  1. Marwa Ben M’barek
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  2. Amel Borgi
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  3. Sana Ben Hmida
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  4. Marta Rukoz
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Corresponding author

Correspondence to Marwa Ben M’barek .

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Editors and Affiliations

  1. Information Systems Group, University of Twente, Enschede, The Netherlands

    Marten van Sinderen

  2. Institute of Business Informatics, Wrocław University of Economics, Wrocław, Poland

    Leszek A. Maciaszek

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Ben M’barek, M., Borgi, A., Ben Hmida, S., Rukoz, M. (2020). GA-PPI-Net: A Genetic Algorithm for Community Detection in Protein-Protein Interaction Networks. In: van Sinderen, M., Maciaszek, L. (eds) Software Technologies. ICSOFT 2019. Communications in Computer and Information Science, vol 1250. Springer, Cham. https://doi.org/10.1007/978-3-030-52991-8_7

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