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Microarray Image Denoising using Independent Component Analysis

by Arunakumari Kakumani, Kaustubha A. Mendhurwar, Rajasekhar Kakumani
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 11
Year of Publication: 2010
Authors: Arunakumari Kakumani, Kaustubha A. Mendhurwar, Rajasekhar Kakumani
10.5120/234-388

Arunakumari Kakumani, Kaustubha A. Mendhurwar, Rajasekhar Kakumani . Microarray Image Denoising using Independent Component Analysis. International Journal of Computer Applications. 1, 11 ( February 2010), 87-93. DOI=10.5120/234-388

@article{ 10.5120/234-388,
author = { Arunakumari Kakumani, Kaustubha A. Mendhurwar, Rajasekhar Kakumani },
title = { Microarray Image Denoising using Independent Component Analysis },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 11 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 87-93 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number11/234-388/ },
doi = { 10.5120/234-388 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:46:07.911503+05:30
%A Arunakumari Kakumani
%A Kaustubha A. Mendhurwar
%A Rajasekhar Kakumani
%T Microarray Image Denoising using Independent Component Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 11
%P 87-93
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

DNA microarrays have proved to be one of the vital breakthrough technologies for exploring the patterns of gene expression on a global scale. The differential measured gene-expression levels depend largely on the probe intensities extracted during microarray image processing. Various noises introduced during the experiment and the imaging process can drastically influence the accuracy of results. Microarray image denoising is one of the challenging pre-processing steps in microarray image analysis. In this paper, we propose denoising of microarray images using the independent component analysis (ICA). The idea of ICA i.e. finding the linear representation of nongaussian data so that the components are independent (or atleast as independent as possible) is exploited for denoising microarray images. Through examples, it is shown that the proposed approach is highly effective as compared to the conventional discrete wavelet transform and statistical methods.

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Index Terms

Computer Science
Information Sciences

Keywords

Denoising independent component analysis microarray image shrinkage function white Gaussian noise

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