• DocumentCode
    2499038
  • Title

    Application of a New Similarity Measure in Clustering Gene Expression Data

  • Author

    Gangguo Li ; Zheng-Zhi Wang ; Qingshan Ni ; Xiaomin Wang ; Bo Qiang ; Han Qing-juan

  • Author_Institution
    Inst. of Autom., Nat. Univ. of Defense Technol., Changsha, China
  • fYear
    2009
  • fDate
    11-13 June 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A new similarity measure for gene expression data, CorHsim, is proposed. It is compared with the other two commonly used measures over some very simple examples. Together with the other two measures, it is implemented in K- means clustering method over two real gene expression data sets. The clustering results show that the CorHsim measure has better performances than the other two measures, which demonstrates that it is a promising measure for gene expression data to discover gene expression patterns.
  • Keywords
    bioinformatics; genetics; pattern clustering; CorHsim; K- means clustering; clustering gene expression data; similarity measure; Automation; Clustering algorithms; Clustering methods; Couplings; Data analysis; Gene expression; Inspection; Noise reduction; Pattern analysis; Performance evaluation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-2901-1
  • Electronic_ISBN
    978-1-4244-2902-8
  • Type

    conf

  • DOI
    10.1109/ICBBE.2009.5162382
  • Filename
    5162382
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2499038