title: Active module identification in intracellular networks using a memetic algorithm with a new binary decoding scheme.
abstract: Active modules are connected regions in biological network which show significant changes in expression over particular conditions. The identification of such modules is important since it may reveal the regulatory and signaling mechanisms that associate with a given cellular response.
  
  
  
  In this paper, we propose a novel active module identification algorithm based on a memetic algorithm. We propose a novel encoding/decoding scheme to ensure the connectedness of the identified active modules. Based on the scheme, we also design and incorporate a local search operator into the memetic algorithm to improve its performance.
  
  
  
  The effectiveness of proposed algorithm is validated on both small and large protein interaction networks.
authors.affiliation: School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK.
authors.forename: Dong
authors.initials: D
authors.lastname: Li
authors.affiliation: PLA University of Science and Technology, Nanjing, 210007, China.
authors.forename: Zhisong
authors.initials: Z
authors.lastname: Pan
authors.affiliation: PLA University of Science and Technology, Nanjing, 210007, China.
authors.forename: Guyu
authors.initials: G
authors.lastname: Hu
authors.affiliation: College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518060, China.
authors.forename: Zexuan
authors.initials: Z
authors.lastname: Zhu
authors.affiliation: School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK. s.he@cs.bham.ac.uk.
authors.forename: Shan
authors.initials: S
authors.lastname: He
mesh_terms: D000465:Algorithms; D053263:Gene Regulatory Networks; D006801:Humans; D025941:Protein Interaction Mapping / Q000706:statistics & numerical data; D060066:Protein Interaction Maps; D015398:Signal Transduction
keywords: Connectedness; Memetic algorithm; Module identification; Module size