Cancer classification based on gene expression using neural networks.

Journal: Genetics and molecular research : GMR
Published Date:

Abstract

Based on gene expression, we have classified 53 colon cancer patients with UICC II into two groups: relapse and no relapse. Samples were taken from each patient, and gene information was extracted. Of the 53 samples examined, 500 genes were considered proper through analyses by S-Kohonen, BP, and SVM neural networks. Classification accuracy obtained by S-Kohonen neural network reaches 91%, which was more accurate than classification by BP and SVM neural networks. The results show that S-Kohonen neural network is more plausible for classification and has a certain feasibility and validity as compared with BP and SVM neural networks.

Authors

  • H P Hu
    School of Science, North University of China, Taiyuan, Shanxi, China.
  • Z J Niu
    School of Science, North University of China, Taiyuan, Shanxi, China.
  • Y P Bai
    School of Science, North University of China, Taiyuan, Shanxi, China.
  • X H Tan
    School of Science, North University of China, Taiyuan, Shanxi, China.