• DocumentCode
    2354518
  • Title

    Mining the Largest Quasi-clique in Human Protein Interactome

  • Author

    Bhattacharyya, Malay ; Bandyopadhyay, Sanghamitra

  • Author_Institution
    Machine Intell. Unit, Indian Stat. Inst., Kolkata, India
  • fYear
    2009
  • fDate
    24-26 Sept. 2009
  • Firstpage
    194
  • Lastpage
    199
  • Abstract
    A clique is a complete subgraph of a graph. Often, a clique is interpreted as a dense module of vertices within a graph. However, in many real-world situations, the classical problem of finding a clique is required to be relaxed. This motivates the problem of finding quasicliques that are almost complete subgraphs of a graph. In sparse and very large scale-free networks, the problem of finding the largest quasi-clique becomes hard to manage with the existing approaches. Here, we propose a heuristic algorithm in this paper for locating the largest quasi-clique from the human protein-protein interaction networks. The results show promise in computational biology research by the exploration of significant protein modules.
  • Keywords
    biology computing; complex networks; data mining; graph theory; computational biology; graph; heuristic algorithm; human protein interactome; human protein-protein interaction networks; quasi-cliques; scale-free networks; subgraphs; Adaptive systems; Computational biology; Computer network management; Heuristic algorithms; Humans; Intelligent systems; Machine intelligence; Organisms; Proteins; Web sites;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Adaptive and Intelligent Systems, 2009. ICAIS '09. International Conference on
  • Conference_Location
    Klagenfurt
  • Print_ISBN
    978-0-7695-3827-3
  • Type

    conf

  • DOI
    10.1109/ICAIS.2009.39
  • Filename
    5329490