Gene Co expression analysis for identifying some regulatory genes in human lung cancer

Cancer occurs owing to significant variances in the gene expression level. Like all cancer lung cancer is the result of abnormalities in the regulatory systems of genes. It is evident that, gene expression systems can successfully frame phenotypes. Hence, it is important to analyze co expressed genes that could shed light on the fundamental principles governing the transcriptional regulatory processes influencing tumor formation and evolution. Oligonucleotide microarray and sequencing technology advancements have made it possible to quickly monitor the expression of genes in different tissues, providing a great mechanism in cancer research domain In the present article we have designed an algorithm which is focused on analyzing the gene correlation values of human lung expression and studying the gene correlation network. The algorithm effectively identifies some regulatory genes having significant association with lung cancer.