By Topic

Simple Software for Microarray Image Analysis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)

A set of microarray images were acquired by a sequence of biological experiments which were scanned via a high resolution scanner. For each spot corresponding to a gene, the ratio of Cy3 and Cy5 fluorescent signal intensities was obtained and which may be normalied based on piecewise linear regression such as lowess method. In this study, we computed from 55 microarray images to get an M × N genematrix, A, with N = 55 patients and M = 13574 effected genes in each microarray. We start with our gene discovery from a genematrix A epsillon R^M×N, M = 13574, N = 55, including N1 = 29 patients of hepatitis B virus (HBV), N2 = 21 patients of hepatitis C virus (HCV), 1 patient clinically diagnosed to be infected with HCV as well as HBV, and 4 patients were neither HCV nor HBV infected. Simple software was developed to solve the following problems: (i) Detect differentially expressed genes and (ii) Select a subset of genes which best distinguishes HBV patients from HCV ones.

Published in:

The 3rd Canadian Conference on Computer and Robot Vision (CRV'06)

Date of Conference:

07-09 June 2006