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MC64-ClustalWP2: a highly-parallel hybrid strategy to align multiple sequences in many-core architectures
David Díaz1, Francisco J Esteban2, Pilar Hernández3
1Dep. Lenguajes y Ciencias de la Computación, Universidad de Málaga, Málaga, Spain.
Plos One
|April 9, 2014
Summary
We developed MC64-ClustalWP2, a faster Clustal W algorithm for aligning long DNA sequences on many-core systems. This bioinformatics tool significantly improves performance for evolutionary and biodiversity studies.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomics
Background:
- Multiple sequence alignment is crucial for bioinformatics.
- Existing Clustal W implementations face performance bottlenecks with long sequences on many-core architectures.
- Optimizing alignment for large datasets is essential for modern biological research.
Purpose of the Study:
- To develop a high-performance implementation of the Clustal W algorithm for many-core systems.
- To enhance the speed and efficiency of aligning long biological sequences.
- To provide a publicly accessible web service for advanced sequence alignment.
Main Methods:
- Developed MC64-ClustalWP2, a novel parallelization strategy for Clustal W.
- Focused optimization on time-consuming stages like progressive alignment, unrolling and parallelizing loops.
- Implemented the algorithm on a hybrid-computing system (Intel Xeon CPU and Tilera Tile64 many-core card).
Main Results:
- MC64-ClustalWP2 achieves significant performance gains on many-core CPUs for long sequences (>10 kb).
- The new implementation runs multiple alignments over 18x faster than original Clustal W and over 7x faster than previous parallel versions.
- The tool is deployable on cost-effective personal computers.
Conclusions:
- MC64-ClustalWP2 offers a substantial performance improvement for large-scale sequence alignment tasks.
- This advancement benefits life-science researchers in areas like mutation analysis, biodiversity, and evolutionary studies.
- The publicly available web service facilitates applications in paternity testing, breeding, and intellectual property protection.
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