Noise reduction from the microarray images to identify the intensity of the expression

Abstract

Microarray technique is used to study the role of genetics involved in the development of diseases in an early stage. Recently microarray has made an enormous contribution to explore the diversemolecular mechanisms involved in tumorigenesis. The end product of microarray is the digital image, whose quality is often degraded by noise caused due to inherent experimental variability. Therefore, noise reduction is a most contributing step involved in the microarray image processing to obtain high intensity gene expression results and to avoid biased results.Microarray data of breast cancer geneswas obtained from National Institute of Animal Science and Rural Development Administration, Suwon, South Korea. Two algorithms were created for noise reduction and to calculate the intensity of gene expression of breast cancer susceptibility gene 1 (BRCA1) and breast cancer susceptibility gene 2 (BRCA2). The new algorithm successively decreased the noise and the expression value of microarray gene image was efficiently enhanced.