Hierarchical Clustering of Differentially Expressed Genes using Up and Down Gene Regulation and Gene Enrichment Analysis in Alzheimer Disease Dataset

ABSTRACT Alzheimer disease is the most common form of dementia in older adults, a general term for memory loss and other brain abilities serious enough to interfere with daily life. The identification of differentially expressed genes among affected brain regions can provide more information about Alzheimer disease. In bioinformatics, differentially expressed gene is the measurement of the activity or expression of genes. Gene expression analysis across various biological conditions, cell cycle states, tissues and subjects may help to identify differentially expressed genes and further Gene Ontology (GO) is used to analyze microarray gene data by using the GO database. In this study, Differentially Expressed Genes (DEGs) in Alzheimer disease dataset are clustered by hierarchical clustering using up and down gene regulation and gene enrichment analysis.