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Parallel Multiple Sequence Alignment with Decentralized Cache Support

  • Denis Trystram
  • Jaroslaw Zola
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3648)

Abstract

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.

Keywords

Multiple Sequence Alignment Multiple Alignment Input Sequence Pairwise Alignment Cache Replacement 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Denis Trystram
    • 1
  • Jaroslaw Zola
    • 1
    • 2
  1. 1.Laboratoire ID–IMAGGrenobleFrance
  2. 2.Institute of Computer & Information SciencesCzestochowa University of TechnologyPoland

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