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International Conference on Parallel Processing and Applied Mathematics

PPAM 2007: Parallel Processing and Applied Mathematics pp 1240–1248Cite as

Protein Similarity Search with Subset Seeds on a Dedicated Reconfigurable Hardware

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 4967)

Abstract

With a sharp increase of available DNA and protein sequence data, new precise and fast similarity search methods are needed for large-scale genome and proteome comparisons. Modern seed-based techniques of similarity search (spaced seeds, multiple seeds, subset seeds) provide a better sensitivity/specificity ratio. We present an implementation of such a seed-based technique on a parallel specialized hardware embedding reconfigurable architecture (FPGA), where the FPGA is tightly connected to large capacity Flash memories. This parallel system allows large databases to be fully indexed and rapidly accessed. Compared to traditional approaches presented by the Blastp software, we obtain both a significant speed-up and better results. To the best of our knowledge, this is the first attempt to exploit efficient seed-based algorithms for parallelizing the sequence similarity search.

Keywords

  • sequence
  • similarity search
  • spaced seeds
  • subset seeds
  • indexing
  • FPGA
  • reconfigurable architecture
  • dedicated hardware

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  • DOI: 10.1007/978-3-540-68111-3_131
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Author information

Authors and Affiliations

  1. Symbiose, IRISA, INRIA, CNRS, Université Rennes 1,  

    Pierre Peterlongo, Dominique Lavenier, Gilles Georges & Julien Jacques

  2. Sequoia/Bioinfo, LIFL, INRIA, CNRS, Université Lille 1,  

    Laurent Noé, Gregory Kucherov & Mathieu Giraud

Authors
  1. Pierre Peterlongo
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  2. Laurent Noé
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  3. Dominique Lavenier
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  4. Gilles Georges
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  5. Julien Jacques
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  6. Gregory Kucherov
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  7. Mathieu Giraud
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    © 2008 Springer-Verlag Berlin Heidelberg

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    Peterlongo, P. et al. (2008). Protein Similarity Search with Subset Seeds on a Dedicated Reconfigurable Hardware. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Wasniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2007. Lecture Notes in Computer Science, vol 4967. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68111-3_131

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    • DOI: https://doi.org/10.1007/978-3-540-68111-3_131

    • Publisher Name: Springer, Berlin, Heidelberg

    • Print ISBN: 978-3-540-68105-2

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