Constructing Evolutionary Tree [Phylogeny] using BIRCH Algorithm

As the number of sequences in the GenBank databasc has increased exponentially, biologists are scrambling to place the information in meaningful context. Researchers try to reconstruct the branching by looking at the similarities and differences of the DNAs of the present day individuals. Phylogeny is the study of the historical pattern of relationships among organisms which has resulted from the actions of many different evolutionary processes. Phylogenetic relationships are depicted by branching diagrams called cladograms or phylogenetic trees. Mining biological data is an emerging area of intersection between bioinformatics and data mining. The data mining techniques are widely used in biology to interpret the information underlying in the sequences. Clustering is a useful data mining technique for the discovery of data distribution and patterns in the data. In this research work an attempt is made to find the evolutionary relationship using a data mining hierarchal agglomerative clustering teclinique. The BIRCH algorithm is implemented to cluster DNA sequences to find the phylogenetic relationship among the organisms