An Algorithm for Clustering Gene Expression Data Using Minimum Spanning Trees

Genes are divided up for computing and understanding the categories of animals and plants and for getting the knowledge about their connatural structures in the research of the biology It is important that using a clustering analysis method, modes of gene expression data are effectively recognized and they are classified as clusters which are formed by similar objects for studying their structure and function, and the relationship between different species of genes Minimum spanning trees, a graph theoretic approach, is used in clustering gene expression data of molecular biology Expression with spanning trees and clustering analysis method based on minimum spanning trees are designed It is proved that optimum clusters can be obtained by using some rule functions Discussion and evaluation are shown for the algorithm, according to the results of the experiments