• DocumentCode
    501722
  • Title

    Finding Time-Delayed Gene Regulation Patterns from Microarray Data

  • Author

    Kuo, Huang-Cheng ; Tsai, Pei-Cheng ; Huang, Jen-Peng

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Eng., Nat. Chiayi Univ., Chiayi, Taiwan
  • Volume
    1
  • fYear
    2009
  • fDate
    12-14 Aug. 2009
  • Firstpage
    117
  • Lastpage
    122
  • Abstract
    Discovered gene regulation networks are very helpful to predict unknown gene functions. Microarray gene expression data reveals activation and deactivation relations among genes. There are evidences showing that multiple time units delay exist in a gene regulation process. Association rule mining technique is very suitable for finding regulation relations among genes. However, current association rule mining techniques can not handle temporally ordered transactions. We propose a modified association rule mining technique for efficiently discovering time-delayed regulation relationships among genes.
  • Keywords
    DNA; biology computing; data handling; data mining; DNA microarray data; gene regulation process; microarray gene expression data; modified association rule mining technique; multiple time unit delay; time-delayed gene regulation pattern; Association rules; Clustering algorithms; DNA; Data analysis; Data mining; Gene expression; Hydrogen; Itemsets; Proteins; RNA; Apriori Algorithm; Association Rule Mining; Gene Regulation; Microarray;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Hybrid Intelligent Systems, 2009. HIS '09. Ninth International Conference on
  • Conference_Location
    Shenyang
  • Print_ISBN
    978-0-7695-3745-0
  • Type

    conf

  • DOI
    10.1109/HIS.2009.31
  • Filename
    5254322