Gene selection using independent variable group analysis for tumor classification

@article{Yan2010GeneSU,
  title={Gene selection using independent variable group analysis for tumor classification},
  author={Qing Yan and Yanwen Chong and Hong-Qiang Wang},
  journal={Neural Computing and Applications},
  year={2010},
  volume={20},
  pages={161-170}
}
Microarrays are capable of detecting the expression levels of thousands of genes simultaneously. So, gene expression data from DNA microarray are characterized by many measured variables (genes) on only a few samples. One important application of gene expression data is to classify the samples. In statistical terms, the very large number of predictors or variables compared to small number of samples makes most of classical “class prediction” methods unemployable. Generally, this problem can be… CONTINUE READING