Abstract
Microarray technique facilitates the generation of large amount of data useful for solving many biological problems. Analyzing this vast amount of data needs more effort due to its huge dimension. Usually, statistical methods like clustering are used to extract the common features among existing informal groups in a microarray data. But, these methods generally need dimensionality reduction and denoising the data for effective utilization and hence better exploratory techniques are required for visualization and analysis. The aim of this paper is to study the capability of transform oriented signal processing techniques especially wavelet transform and wavelet power spectrum to study characteristics of microarray data .The suitability of wavelet based technique has been demonstrated on such datasets and the behaviors of various samples as well as genes were studied. It was also found that the proposed technique is more efficient and requires no extensive preprocessing.