Discrete Wavelet Transform Based Feature Extraction for Tissue Classification Using Gene Expression Data

DNA microarrays can be used to measure the expression levels of thousands of genes simultaneously. In this paper, the gene expression data were processed by a signal processing method. A discrete wavelet transform (DWT) based feature extraction method for cancer classification was introduced, by which micro-array data are transformed into time-scale domain and used as classification features. Finally, some test and comparison experiments for the feature extraction method have been made by using the weighted voting classification scheme(1). Experiment results show that the correct rate is over 90% in tumor vs normal classification by using the feature extraction method.