Data processing in DNA microarray is a critical step that transforms raw fluorescence signals into meaningful biological information. A DNA microarray experiment measures the expression levels of thousands of genes simultaneously by hybridizing labeled nucleic acid samples to complementary DNA probes fixed on a solid surface. The quality and reliability of the final results depend heavily on accurate data processing methods. The entire process involves several sequential steps, including image acquisition, feature extraction, quality assessment, normalization, statistical analysis, and biological interpretation. The first stage of data processing begins with image acquisition. After hybridization and washing, the microarray slide is scanned using a laser scanner. The fluorescent dyes attached to the sample emit light at specific wavelengths, and the scanner captures high-resolution images. In two-color microarrays, two fluorescent dyes such as Cy3 (green) and Cy5 (red) are commonly used, while single-color microarrays measure fluorescence from one dye only. These images serve as the raw data for further analysis. The next step is feature extraction. Specialized software identifies each spot on the microarray and measures its fluorescence intensity. Every spot corresponds to a specific gene or DNA sequence. The software calculates the foreground intensity, representing the true signal, and