Implementing Phylogenetic Distance Based Methods for Tree Construction Using Hierarchical Clustering
Journal Title: International Journal of Computer Science & Engineering Technology - Year 2013, Vol 4, Issue 7
Abstract
Bioinformatics is a data intensive field of research and development. Key problem of knowledge discovery from large and complex databases is deal problem data mining. It is used to discover relationships and patterns in large databases to provide useful information. Clustering is the one of the main techniques for data mining. Phylogeny is the evolutionary history for a set of evolutionary related species. Diagrams that display the phylogeny of a set of taxa in a tree like manner are called phylogenetic trees. One approach on determining the evolutionary histories of a dataset are distance based methods. There are number of different distance based methods of which two are dealt with here: the UPGMA (Unweighted Pair Group Method using Arithmetic average) and Neighbor Joining. These two are clustering based methods. A method for construction of distance based phylogenetic tree using hierarchical clustering is proposed and implemented on different Oryza sativa rice varieties. The sequences are downloaded from NCBI databank. Evolutionary distances are calculated using jukes cantor distance method. Multiple sequence alignment is applied on different datasets. Trees are constructed for different datasets from available data using both the distance based methods. Extractions of closely related varieties are performed by applying threshold condition. Then, final tree is constructed using these closely related varieties.
Authors and Affiliations
Archi Kataria , Dr. Amardeep Singh
Keywords
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