| Microarray technology is a newly emerging technique that promises revolutionary progress in better health and improved quality of life. This dissertation focuses on the development of a user-friendly and efficient software package (named SmartArray), equipped with existing methods and new methods proposed in this dissertation, that will allow processing and analysis of thousands of genes on microarray images. New methods proposed include a template alignment method using a DAC algorithm, an adaptive threshold algorithm, a wavelet denoising algorithm for background removal, a snake algorithm using minimum SS (Sum of Squares), and a quality of printing method. Novel methods of analysis are proposed for the optimization of microarray applications.; SmartArray has three tools: a template alignment tool, a quantification tool, and an analysis tool. The processing and analysis are performed sequentially regardless of the type of microarray images. First, scanned microarray images are corrected in the preprocessing step if they are tilted. Then, circle templates are placed on the spots in microarray images using MCF (Microarray Configuration File) files, and the spots are quantified by user-defined methods. Finally, the gene expression data from a control microarray and a test microarray is compared and analyzed for gene analysis.; The analysis results demonstrate that the software package can find many changes in gene expression levels in each subarray and can classify them according to their significance. In addition, the changed genes correspond to visual comparisons through charts of each subarray. The results of analysis of the microarray images are obtained through newly proposed methods, which worked well for our desired goals and tell which genes in a test microarray are significantly up- or downregulated compared to genes in a control microarray. |
