• DocumentCode
    3194209
  • Title

    Mining protein complexes based on connected affinity clique extension

  • Author

    Peng Li ; Xiaohua Hu ; Tingting He ; Junmin Zhao ; Ming Zhang ; Xianjun Shen

  • Author_Institution
    Sch. of Comput., Central China Normal Univ., Wuhan, China
  • fYear
    2013
  • fDate
    18-21 Dec. 2013
  • Firstpage
    53
  • Lastpage
    56
  • Abstract
    A novel algorithm based on Connected Affinity Clique Extension (CACE) for mining overlapping functional modules in protein interaction network is proposed in this paper. In this approach, the value of protein connected affinity is interpreted as the reliability and possibility of interaction which is inferred from protein complexes. The protein interaction network is constructed as a weighted graph, and the weigh is dependent on the connected affinity coefficient. The experimental results of our CACE in two test data sets show that the CACE can detect the functional modules much more effective and accurate compared with other state-of-art algorithms CPM and IPC-MCE.
  • Keywords
    bioinformatics; molecular biophysics; proteins; CACE algorithm; CPM algorithm; Connected Affinity Clique Extension; IPC-MCE algorithm; connected affinity coefficient; overlapping functional modules mining; protein complexes; protein interaction network; reliability; weighted graph; Algorithm design and analysis; Bioinformatics; Clustering algorithms; Communities; Protein engineering; Proteins; Algorithm CACE; Connected affinity; Overlapping functional modules; effective and accurate;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine (BIBM), 2013 IEEE International Conference on
  • Conference_Location
    Shanghai
  • Type

    conf

  • DOI
    10.1109/BIBM.2013.6732459
  • Filename
    6732459