Heuristic Modularity for Complex Identification in Protein-Protein Interaction Networks

  • Amenah H. H. Abdulateef Department of Computer Science, College of Education for Pure Science (Ibn al-Haitham), University of Baghdad, Iraq
  • Bara'a A. Attea Department of Computer Science, College of Science, University of Baghdad, Baghdad, Iraq
  • Ahmed N. Rashid Computers and Information Technology, University of Anbar, Anbar, Iraq

Abstract

     Due to the significant role in understanding cellular processes, the decomposition of Protein-Protein Interaction (PPI) networks into essential building blocks, or complexes, has received much attention for functional bioinformatics research in recent years. One of the well-known bi-clustering descriptors for identifying communities and complexes in complex networks, such as PPI networks, is modularity function.   The contribution of this paper is to introduce heuristic optimization models that can collaborate with the modularity function to improve its detection ability. The definitions of the formulated heuristics are based on nodes and different levels of their neighbor properties.  The modularity function and the formulated heuristics are then injected into the mechanism of a single objective Evolutionary Algorithm (EA) tailored specifically to tackle the problem, and thus, to identify possible complexes from PPI networks. In the experiments, different overlapping scores are used to evaluate the detection accuracy in both complex and protein levels. According to the evaluation metrics, the results reveal that the introduced heuristics have the ability to harness the accuracy of the existing modularity while identifying protein complexes in the tested PPI networks.

Published
Aug 26, 2019
How to Cite
H. ABDULATEEF, Amenah H.; ATTEA, Bara'a A.; RASHID, Ahmed N.. Heuristic Modularity for Complex Identification in Protein-Protein Interaction Networks. Iraqi Journal of Science, [S.l.], p. 1846-1859, aug. 2019. ISSN 2312-1637. Available at: <http://scbaghdad.edu.iq/eijs/index.php/eijs/article/view/1084>. Date accessed: 17 sep. 2019.
Section
Computer Science