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Phylogenetic Predictions on Grids

Katariya, PR and Vadhiyar, SS (2009) Phylogenetic Predictions on Grids. In: In proceedings of the 5th IEEE International Conference of e-Science, 9-11 Dec. 2009, Oxford.

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A phylogenetic or evolutionary tree is constructed from a set of species or DNA sequences and depicts the relatedness between the sequences. Predictions of future sequences in a phylogenetic tree are important for a variety of applications including drug discovery, pharmaceutical research and disease control. In this work, we predict future DNA sequences in a phylogenetic tree using cellular automata. Cellular automata are used for modeling neighbor-dependent mutations from an ancestor to a progeny in a branch of the phylogenetic tree. Since the number of possible ways of transformations from an ancestor to a progeny is huge, we use computational grids and middleware techniques to explore the large number of cellular automata rules used for the mutations. We use the popular and recurring neighbor-based transitions or mutations to predict the progeny sequences in the phylogenetic tree. We performed predictions for three types of sequences, namely, triose phosphate isomerase, pyruvate kinase, and polyketide synthase sequences, by obtaining cellular automata rules on a grid consisting of 29 machines in 4 clusters located in 4 countries, and compared the predictions of the sequences using our method with predictions by random methods. We found that in all cases, our method gave about 40% better predictions than the random methods.

Item Type: Conference Paper
Publisher: IEEE
Additional Information: Copyright 2009 IEEE. Personal use of this material is permitted.However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre: Division of Interdisciplinary Sciences > Supercomputer Education & Research Centre
Date Deposited: 13 Dec 2011 11:49
Last Modified: 13 Dec 2011 11:49
URI: http://eprints.iisc.ac.in/id/eprint/41286

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