SWPS3: A Fast Implementation of the Smith-Waterman Algorithm
Author Information
Author(s): Adam Szalkowski, Christian Ledergerber, Philipp Krähenbühl, Christophe Dessimoz
Primary Institution: ETH Zürich
Hypothesis
Can the Smith-Waterman local alignment algorithm be optimized for better performance on different architectures?
Conclusion
The SWPS3 implementation demonstrates that the Cell/BE can effectively align biological sequences, achieving performance levels comparable to heuristic methods.
Supporting Evidence
- SWPS3 is the fastest implementation of the Smith-Waterman algorithm on the Cell/BE, outperforming previous implementations by a factor of at least 4.
- On a quad-core Intel Pentium, SWPS3 achieves up to 15.7 billion cell-updates per second.
- SWPS3's performance is comparable to heuristic methods like BLAST for long protein sequences.
Takeaway
This study shows a new tool that helps compare biological sequences really fast, making it easier for scientists to understand how they are related.
Methodology
The study involved benchmarking the SWPS3 implementation against other alignment tools using protein sequences and various scoring matrices.
Limitations
SWPS3 can only compute local protein sequence alignments with affine gaps and does not display the resulting alignment.
Digital Object Identifier (DOI)
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