• DocumentCode
    2010488
  • Title

    Classification of Scleroderma and Normal Biopsy Data and Identification of Possible Biomarkers of the Disease

  • Author

    Paul, Topon Kumar ; Iba, Hitoshi

  • Author_Institution
    Graduate Sch. of Frontier Sci., Tokyo Univ., Chiba
  • fYear
    2006
  • fDate
    28-29 Sept. 2006
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Scleroderma is an autoimmune disease of the connective tissues, which thickens and hardens the affected areas. Recently, researchers have found evidence that genes are important factors for this disease, and there exist consistent differences in the patterns of gene expressions of skin biopsies from affected and non-affected individuals. In this paper, we apply genetic programming (GP) on the gene expression data of scleroderma and normal biopsies to evolve the classification rules that can differentiate between them. In these evolved rules, we have found six genes that have differential gene expression levels in scleroderma and normal biopsies and thus individually can classify all the samples correctly. In addition to these genes, we have also found some simple rules containing two or more genes that can classify all the samples perfectly
  • Keywords
    biology computing; diseases; genetic algorithms; molecular biophysics; pattern classification; skin; autoimmune disease; biomarkers; classification rules; connective tissues; gene expressions; genetic programming; normal biopsy data; scleroderma; skin biopsies; Biomarkers; Biopsy; Blood vessels; Diseases; Evolutionary computation; Gene expression; Genetic programming; Skin; Support vector machine classification; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Bioinformatics and Computational Biology, 2006. CIBCB '06. 2006 IEEE Symposium on
  • Conference_Location
    Toronto, Ont.
  • Print_ISBN
    1-4244-0623-4
  • Electronic_ISBN
    1-4244-0624-2
  • Type

    conf

  • DOI
    10.1109/CIBCB.2006.330951
  • Filename
    4133187