Protein Similarity Search with Subset Seeds on a Dedicated Reconfigurable Hardware
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.
Keywordssequence similarity search spaced seeds subset seeds indexing FPGA reconfigurable architecture dedicated hardware
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