A new kind of science
DNA sequence evolution with neighbor-dependent mutation
Proceedings of the sixth annual international conference on Computational biology
Regular biosequence pattern matching with cellular automata
Information Sciences—Applications: An International Journal
HPDC '03 Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing
A Performance Study of Monitoring and Information Services for Distributed Systems
HPDC '03 Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing
A Global Grid for Analysis of Arthropod Evolution
GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
The Globus Striped GridFTP Framework and Server
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Globus toolkit version 4: software for service-oriented systems
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
Morco: middleware framework for long-running multi-component applications on batch grids
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
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Study of the evolution of species or organisms is essential for various biological applications. Evolution is typically studied at the molecular level by analyzing the mutations of DNA sequences of organisms. Techniques have been developed for building phylogenetic or evolutionary trees for a set of sequences. Though phylogenetic trees capture the overall evolutionary relationships among the sequences, they do not reveal fine-level details of the evolution. In this work, we attempt to resolve various fine-level sequence transformation details associated with a phylogenetic tree using cellular automata. In particular, our work tries to determine the cellular automata rules for neighbor-dependent mutations of segments of DNA sequences. We also determine the number of time steps needed for evolution of a progeny from an ancestor and the unknown segments of the intermediate sequences in the phylogenetic tree. Due to the existence of vast number of cellular automata rules, we have developed a grid system that performs parallel guided explorations of the rules on grid resources. We demonstrate our techniques by conducting experiments on a grid comprising machines in three countries and obtaining potentially useful statistics regarding evolutions in three HIV sequences. In particular, our work is able to verify the phenomenon of neighbor-dependent mutations and find that certain combinations of neighbor-dependent mutations, defined by a cellular automata rule, occur with greater than 90% probability. We also find the average number of time steps for mutations for some branches of phylogenetic tree over a large number of possible transformations with standard deviations less than 2.