METHODS USED FOR IDENTIFICATION OF DIFFERENTIALLY EXPRESSING GENES (DEGS) FROM MICROARRAY GENE DATASET: A REVIEW

Genes contain blue print of living organism. Malfunctioning occurred in cellular life is indicated byproteins which are responsible for behavior of genes. Fixed set of genes decides behavior and functioningof cells. They guide the cells what to do and when to do. To analyze the insight of biological activities,analysis of gene expressions is necessary. Advanced technology like microarray plays an important role ingene analysis as it captures expressions of thousands of genes under different conditions simultaneously.Out of thousands of genes, very few behave differently which are called as Differentially Expressing Genes(DEGs). Identifying these most significant genes is a crucial task in molecular biology and is a major areaof research for bioinformaticians because DEGs are the major source of disease prediction. They help inplanning therapeutic strategies for a disease through Gene Regulatory Network (GRN) constructed fromthem. GRN is a graphical representation containing genes as nodes and regulatory interactions amongthem as edges. GRN helps to know change over occurred among genes which involved in cause of geneticdiseases as well as to analyze their response to different stress conditions through microarray expressions.In this paper we have discussed many methods proposed by researchers for identifying differentiallyexpressing genes based upon changes in their expressions patterns.