• DocumentCode
    1974385
  • Title

    Classification of cancer gene expressions from micro-array analysis

  • Author

    Venkatesh, E.T. ; Tangaraj, P. ; Chitra, S.

  • Author_Institution
    Dept. of Comput. Technol., Kongu Eng. Coll., Erode, India
  • fYear
    2010
  • fDate
    12-13 Feb. 2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The role of micro array expression data in cancer diagnosis is very significant. Mining for useful information from such micro array data consisting of thousands of genes and a small number of samples is often a tough task. Colon cancer is the second most common cause of cancer mortality in Western countries. According to the WHO 2006 report colorectal cancer causes 655,000 deaths worldwide per year. All the genes used in the expression profile are not informative; also many of them are redundant. Reducing the number of genes by feature selection and still retaining best class prediction accuracy for the classifier is vital in case of tumor classification. The emphasis in cancer classification is both on methods of gene selection and on choice of classifier. It is proposed to study various classification algorithms.
  • Keywords
    bioinformatics; cancer; data mining; medical computing; neural nets; pattern clustering; support vector machines; WHO; cancer gene expressions classification; cancer mortality; colon cancer; colorectal cancer; feature selection; gene selection; microarray analysis; tumor classification; Bioinformatics; Cancer; Colon; Data mining; Educational institutions; Gene expression; Neoplasms; RNA; Support vector machine classification; Support vector machines; DNA; RNA; Regression Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Computing Technologies (ICICT), 2010 International Conference on
  • Conference_Location
    Tamil Nadu
  • Print_ISBN
    978-1-4244-6488-3
  • Type

    conf

  • DOI
    10.1109/ICINNOVCT.2010.5440095
  • Filename
    5440095