A New Gene Expression Profiles Classifying Approach Based on Neighborhood Rough Set and Probabilistic Neural Networks Ensemble

  • Jiang Yun
  • Xie Guocheng
  • Chen Na
  • Chen Shan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8227)


With the advancement of bioinformatics, the research on the gene chips has been paid more attention by the researchers in recent years. Applications of gene expression profiles on cancer diagnosis and classification have gradually become one of the hot topics in the field of bioinformatics. According to the gene expression profiles characteristics of high dimension and small sample set, we propose a classify method for cancer classification, which is based on neighborhood rough set theory and probabilistic neural network ensemble classification algorithm. Firstly, genes are sorted by using Relief algorithm. Then, classification informative genes are selected using the neighborhood rough set theory. At last, we do cancer classification with probabilistic neural networks ensemble classification model. The experimental results show that the proposed method can effectively select cancer genes, and can obtain better classification results.


Gene Expression Profiles Neighborhood Rough Set Probabilistic Neural Networks Ensemble Classification Algorithm 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jiang Yun
    • 1
  • Xie Guocheng
    • 1
  • Chen Na
    • 1
  • Chen Shan
    • 1
  1. 1.College of Computer Science and EngineeringNorthwest Normal UniversityLanzhouP.R. China

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