الفهرس 
An enhanced approach for mining gene expression data
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Abstract
Cancer refers to a group of diseases characterized by uncontrolled cell growth. Oncogenes and tumor suppressor are two main types of genes that play a role in the development of cancer. Oncogenes tell cells when to divide and tumor suppressor genes tell cells when not to divide. DNA damage and mutation lead to uncontrolled growth of cells (cancer), the result is that damaged genes are responsible for cell division. It seems likely that high throughput gene expression analyses will lead to identify the significant cancer related genes. A historical role for DNA methylation has been in cancer research, especially in the search for abnormally hypermethylated tumor suppressor or hypomethylated oncogenes genes. DNA methylation have been associated with cancer in several investigations. DNA methylation might play an important role in the gene expression regulation. DNA methylation can be measured with Illumina microarrays, the analysis of DNA methylation data leads to identify the most significant genes which are responsible for causing cancer. Also the visualization of DNA methylation status leads to discover very important relationships between hypermethylated and hypomethylated genes