Enhanced Hierarchical Clustering for Gene Expression Data
Micro arrays are used to assess the transcriptome of many biological systems that has generated an enormous amount of data. Cluster analysis is a technique used to group and analyze micro array data. Identification of groups of genes that manifest similar expression patterns is a key step in the analysis of gene expression data. Hierarchical clustering is the one of the clustering techniques used for this purpose. In this paper, the authors design an enhanced hierarchical clustering algorithm which scans the dataset and calculates distance matrix only once unlike other papers, (up to authors' knowledge). Their main contribution is to reduce time, even when a large database is analyzed.