Aligning sequences via an evolutionary tree: complexity and approximation
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Improving Performance of Multiple Sequence Alignment Analysis in Multi-Client Environments
IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
An overview of web caching replacement algorithms
IEEE Communications Surveys & Tutorials
Semantic caching for pervasive grids
IDEAS '09 Proceedings of the 2009 International Database Engineering & Applications Symposium
Cache sémantique pour grilles pervasives
Proceedings of the 5th French-Speaking Conference on Mobility and Ubiquity Computing
Parallel multiple sequence alignment with local phylogeny search by simulated annealing
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
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In this paper we present a new method for aligning large sets of biological sequences. The method performs a sequence alignment in parallel and uses a decentralized cache to store intermediate results. The method allows alignments to be recomputed efficiently when new sequences are added or when alignments of different precisions are requested. Our method can be used to solve important biological problems like the adaptive update of a complete evolution tree when new sequences are added (without recomputing the whole tree). To validate the method, some experiments were performed using up to 512 Small Subunit Ribosomal RNA sequences, which were analyzed with different levels of precision.