Determination of prognosis in breast cancer patients from dna microarray analysis using genetic algorithm

Breast cancer is a serious disease that can cause death. Early diagnosis of breast cancer has been playing very important role on treatment of the disease. Therefore, it is important to find the genes that are relevant to a diagnosis. Recently, microarray technology has been widely used in cancer diagnosis. A microarray is a tool for analyzing gene expression. Microarray data usually contain thousands of genes and a small number of samples. Although, most of them are irrelevant or insignificant to a clinical diagnosis. It is very difficult to obtain a satisfactory classification result by machine learning techniques because of both the curse-of dimensionality problem and the over-fitting problem. Feature selection plays a crucial role in microarray analysis. Feature selection is the process of choosing the most discriminative features so as to enable the classifier to perform better.In this work, a new feature selection method for breast cancer classification based on filter method and genetic algorithm is presented. The study consists of two steps: In the first step, the dimensionality of the gene expression dataset was reduced with filter method and the second step, significant genes have been identified with genetic algorithm. SVM was used for fitness function in genetic programming. In this study the classification accuracy rate was obtained as 96.15% when using the selected 7 genes.