Classification of scleroderma and normal biopsy data and identification of possible biomarkers of the disease

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@InProceedings{paul:2006:cibcb,
  author =       "Topon Kumar Paul and Hitoshi Iba",
  title =        "Classification of scleroderma and normal biopsy data
                 and identification of possible biomarkers of the
                 disease",
  booktitle =    "Proceedings of {IEEE Symposium on Computational
                 Intelligence in Bioinformatics and Computational
                 Biology 2006 (CIBCB2006)}",
  year =         "2006",
  pages =        "306--311",
  address =      "Toronto, Ontario, Canada",
  month =        sep # " 28-29",
  organization = "IEEE Computational Intelligence Society",
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, pattern
                 recognition and classification, scleroderma,
                 biomarkers, majority voting",
  URL =          "http://www.iba.k.u-tokyo.ac.jp/~topon/Papers/CIBCB2006.pdf",
  DOI =          "doi:10.1109/CIBCB.2006.330951",
  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.",
  notes =        "http://eldar.mathstat.uoguelph.ca/dashlock/CIBCB2006/home.html",
}

Genetic Programming entries for Topon Kumar Paul Hitoshi Iba

Citations