An Improved Edge Set Enrichment Analysis Method for Improving Classification Accuracy: Array

Genome-wide expression analysis with DNA microarrays has become a routine tool in biomedical research. Therefore, a various powerful analytical method for pathway- identification has been introduced. However, extracting biological insight from such information remains a challenge. Current pathway-identification methods focus only on the changes in gene expression levels, neglecting biological relationships among genes such as dysregulated relationships. Hence, a more powerful computational method is proposed that is the Edge Set Enrichment Analysis (ESEA) method. ESEA method takes into consideration both changes of gene expression levels and dysregulated relationships among genes that may also the pathway activities. An improved ESEA method in identifying the dysregulated pathway able to increase cancer classification accuracy.