Guided self-scheduling: A practical scheduling scheme for parallel supercomputers
IEEE Transactions on Computers
Aligning sequences via an evolutionary tree: complexity and approximation
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
A scalable content-addressable network
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
An Efficient Program for Phylogenetic Inference Using Simulated Annealing
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 7 - Volume 08
Parallel multiple sequence alignment with decentralized cache support
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
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The problem of multiple sequence alignment is one of the most important problems in computational biology. In this paper we present a new method that simultaneously performs multiple sequence alignment and phylogenetic tree inference for large input data sets. We describe a parallel implementation of our method that utilises simulated annealing metaheuristic to find locally optimal phylogenetic trees in reasonable time. To validate the method, we perform a set of experiments with synthetic as well as real-life data.