• DocumentCode
    1932674
  • Title

    Application of Improved K-mean Clustering in Predicting Protein-Protein Interactions

  • Author

    Sun, Pingping ; Ma, Yanan ; Wei, Yazhuo ; Ma, Zhiqiang ; Lu, Linying ; Cui, Ying ; Huang, Ping

  • Author_Institution
    Sch. of Comput., Northeast Normal Univ., Changchun
  • Volume
    1
  • fYear
    2008
  • fDate
    27-30 May 2008
  • Firstpage
    83
  • Lastpage
    86
  • Abstract
    With the increasing availability of complete genome sequences, there are more excellent opportunity for further research and development of tools for functional studies in proteomics. Phylogenetic profile is a basic non-homology method in functional proteomics. This paper describes the theory of phylogenetic profile, focuses on the improvement of K-mean clustering algorithm in analyzing the protein phylogenetic profile; also compare the method with the traditional K-mean clustering algorithm. The experimental results show that the improved K-mean clustering algorithm is fast and effective; it can quickly converge to the approximate optimal solution.
  • Keywords
    biology computing; molecular biophysics; proteins; K-mean clustering algorithm; functional proteomics; genome sequences; nonhomology method; phylogenetic profile; protein-protein interactions; Algorithm design and analysis; Bioinformatics; Clustering algorithms; Evolution (biology); Genomics; Iterative algorithms; Organisms; Phylogeny; Proteins; Proteomics; improved K-mean clustering; phylogenetic profile; protein-protein interactions;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    BioMedical Engineering and Informatics, 2008. BMEI 2008. International Conference on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-0-7695-3118-2
  • Type

    conf

  • DOI
    10.1109/BMEI.2008.82
  • Filename
    4548640