Methods used for Identification of Differentially Expressing Genes (DEGs) from Microarray Gene Dataset: A Review

 
 
International Journal of Biotech Trends and Technology (IJBTT)
 
© 2017 by IJBTT Journal
Volume - 7 Issue - 2                          
Year of Publication : 2017
Authors : Chanda Panse (Wajgi), Manali Kshirsagar, Dipak Wajgi
  10.14445/22490183/IJBTT-V21P601

Chanda Panse(Wajgi), Manali Kshirsagar, Dipak Wajgi "Methods used for Identification of Differentially Expressing Genes (DEGs) from Microarray Gene Dataset: A Review", International Journal of Biotech Trends and Technology (IJBTT), V7(2): 1-6 Apr to Jun 2017, Published by Seventh Sense Research Group.

Abstract

Genes contain blue print of living organism. Malfunctioning occurred in cellular life is indicated by proteins which are responsible for behavior of genes. Fixed set of genes decides behavior and functioning of 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 in gene analysis. 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 Expressed Genes (DEGs). Identification of these most significant genes is a crucial task in molecular biology and is a major area of research for bioinformaticians because DEGs are the major source of disease prediction. They help in planning therapeutic strategies for a disease through Gene Regulatory Network (GRN) which is constructed from them. GRN is a graphical representation containing genes as nodes and regulatory interactions between them as edges. GRN helps in knowing how genes regulate each other and in sense maintain underlined state of art working of cells. Deregulation between genes is the cause of major genetic diseases. In this paper we have discussed many methods proposed by researchers for identifying differentially expressing genes based upon changes in their expressions patterns.

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Keywords
Gene Regulatory Network (GRN), gene expressions, differentially expressed gene.