Discovery of Biomarkers for Hexachlorobenzene Toxicity Using Population Based Methods on Gene Expression Data

Meydan C., Kuecuekural A., Yoeruekoglu D., Sezerman O. U.

3rd IAPR International Conference on Pattern Recognition in Bioinformatics, Melbourne, Avustralya, 15 - 17 Ekim 2008, cilt.5265, ss.412-423 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 5265
  • Doi Numarası: 10.1007/978-3-540-88436-1_35
  • Basıldığı Şehir: Melbourne
  • Basıldığı Ülke: Avustralya
  • Sayfa Sayıları: ss.412-423
  • Anahtar Kelimeler: Feature selection, toxicogenomics, genetic algorithms, biomarker discovery, MICROARRAY, TOXICOGENOMICS, GENOMICS, INJURY, TOOL
  • Acıbadem Mehmet Ali Aydınlar Üniversitesi Adresli: Hayır

Özet

Discovering toxicity biomarkers is important in drug discovery to safely evaluate possible toxic effects of a substance in early phases. We tried evolutionary classification methods for selecting the important classifier genes in hexachlorobenzene toxicity using microarray data. Using modified genetic algorithms for selection of minimum number of features for classification of gene expression data, we discovered a number of gene sets of size 4 that were able to discriminate between the control and the hexachlorobenzene (HCB) exposed group of Brown-Norway rats with >99% accuracy in 5-fold cross-validation tests, whereas classification using all of the genes with SVM and other methods yielded results that vary between 48.48% to 81.81%. Making use of this small number of genes as biomarkers may allow us to detect toxicity of substances with mechanisms of toxicity similar to HCB in a fast and cost efficient manner when there are no emerging symptoms.