title: Protein complexes predictions within protein interaction networks using genetic algorithms.
abstract: BACKGROUND
  Protein-protein interaction networks are receiving increased attention due to their importance in understanding life at the cellular level. A major challenge in systems biology is to understand the modular structure of such biological networks. Although clustering techniques have been proposed for clustering protein-protein interaction networks, those techniques suffer from some drawbacks. The application of earlier clustering techniques to protein-protein interaction networks in order to predict protein complexes within the networks does not yield good results due to the small-world and power-law properties of these networks.
  
  
  RESULTS
  In this paper, we construct a new clustering algorithm for predicting protein complexes through the use of genetic algorithms. We design an objective function for exclusive clustering and overlapping clustering. We assess the quality of our proposed clustering algorithm using two gold-standard data sets.
  
  
  CONCLUSIONS
  Our algorithm can identify protein complexes that are significantly enriched in the gold-standard data sets. Furthermore, our method surpasses three competing methods: MCL, ClusterOne, and MCODE in terms of the quality of the predicted complexes. The source code and accompanying examples are freely available at http://faculty.kfupm.edu.sa/ics/eramadan/GACluster.zip .
authors.affiliation: Department of Information and Computer Science, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia. eramadan@kfupm.edu.sa.
authors.forename: Emad
authors.initials: E
authors.lastname: Ramadan
authors.affiliation: Department of Information and Computer Science, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
authors.forename: Ahmed
authors.initials: A
authors.lastname: Naef
authors.affiliation: Department of Information and Computer Science, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
authors.forename: Moataz
authors.initials: M
authors.lastname: Ahmed
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D030562:Databases, Protein; D025941:Protein Interaction Mapping / Q000379:methods*; D060066:Protein Interaction Maps
keywords: Genetic algorithms; Graph clustering; Protein complex detection; Protein–protein interaction network