• DocumentCode
    2453451
  • Title

    Comparative Analysis of DNA Microarray Data through the Use of Feature Selection Techniques

  • Author

    Dittman, David J. ; Khoshgoftaar, Taghi M. ; Wald, Randall ; Van Hulse, Jason

  • Author_Institution
    Florida Atlantic Univ., Boca Raton, FL, USA
  • fYear
    2010
  • fDate
    12-14 Dec. 2010
  • Firstpage
    147
  • Lastpage
    152
  • Abstract
    One of today´s most important scientific research topics is discovering the genetic links between cancers. This paper contains the results of a comparison of three different cancers (breast, colon, and lung) based on the results of feature selection techniques on a data set created from DNA micro array data consisting of samples from all three cancers. The data was run through a set of eighteen feature rankers which ordered the genes by importance with respect to a targeted cancer. This process was repeated three times, each time with a different target cancer. The rankings were then compared, keeping each feature ranker static while varying the cancers being compared. The cancers were evaluated both in pairs and all together, for matching genes. The results of the comparison show a large correlation between the two known hereditary cancers, breast and colon, and little correlation between lung cancer and the other cancers. This is the first study to apply eighteen different feature rankers in a bioinformatics case study, eleven of which were recently proposed and implemented by our research team.
  • Keywords
    DNA; bioinformatics; cancer; data mining; lung; DNA microarray data; bioinformatics; breast cancer; colon cancer; feature selection technique; lung cancer; Breast; Cancer; Colon; Lungs; Measurement; Probes; Radio frequency; Breast Cancer; Colon Cancer; DNA Microarray Data; Feature Selection; Lung Cancer;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications (ICMLA), 2010 Ninth International Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    978-1-4244-9211-4
  • Type

    conf

  • DOI
    10.1109/ICMLA.2010.29
  • Filename
    5708826