• DocumentCode
    2520681
  • Title

    Strong Association Rules Mining Without Using Frequent Items for Microarray Analysis

  • Author

    Wang, Miao ; Shang, Xuequn ; Zhao, Qian ; Li, Zhanhuai

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Northwestern Polytech. Univ., Xian, China
  • fYear
    2009
  • fDate
    11-13 June 2009
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Microarray technology has created a revolution in the field of biological research. Association rules can not only group the similarly expressed genes but also discern relationships among genes. However, the efficiency of traditional method to generate association rules is not very well. We develop a novel algorithm, SAW, to generate strong association rules by combining the paired rules, which can avoid lots of unnecessary computing that traditional method often encounter. The experiments show our method is more efficiently than FARMER.
  • Keywords
    biology computing; data mining; genetics; association rules mining; expressed genes; frequent pattern mining; microarray analysis; paired rules; Aging; Association rules; Biological processes; Computer science; Data analysis; Data mining; Electronic mail; Gene expression; Protein engineering; Surface acoustic waves;
  • 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.2009.5163431
  • Filename
    5163431