Abstract
Microarray technology has been recently adopted in molecular biology to screen thousands of genes simultaneously and discover the potential genes which are related to a number of diseases such as breast cancer, gastric cancer, hepatoma, and etc. The computation for gene expression is one of the most important parts in the whole processing. The more accurate gene expression one gets, the more significant results of analysis one reaches. The purpose of this thesis is to provide a flowchart for dealing with microarray image pattern analysis fast, accurately and repeatedly with the emphasis on the computation of gene expression. First, we provide three different methods, Otsu, GMM and ICM, to do gene expression computation. Then do normalization on MA plot to eliminate systematic variations by using two normalization methods: LOWESS and Moving Average Filter. After normalization, we select up-regulated and down-regulated genes for further analysis.