Survey on gene selection methodologies based on filter, wrapper, embedded and hybrid approaches

Gene selection has become a most elementary tool for processing high dimensional data. It is an important pre-processing step which is essential for microarray analysis and classification. DNA microarray technique is applied for analyzing large number of genes at a time, by which the expression levels of the genes are determined. Selection of genes applying high dimensional gene expression data is primary and most important work for accurate disease prediction and classification. Gene expression data are in the form of matrix and usually it contains irrelevant, redundant and noisy data, so the study and analysis of data faces problematic situation. Most important and primary purpose of gene selection methods is to get rid of from the problem of curse of dimensionality, enhance the performance and efficiency of classification algorithms by eliminating irrelevant genes and reduction of noise. This paper describes the various gene selection methods declaring with their relevant pros and cons. It also denotes a review on few gene selection methods, mainly those that have been proposed in last few years.