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SW#–GPU-enabled exact alignments on genome scale
Summary: We propose SW#, a new CUDA graphical processor unit-enabled and memory-efficient implementation of dynamic programming algorithm, for local alignment. It can be used as either a stand-alone application or a library. Although there are other graphical processor unit implementations of the Sm...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3777108/ https://www.ncbi.nlm.nih.gov/pubmed/23864730 http://dx.doi.org/10.1093/bioinformatics/btt410 |
Sumario: | Summary: We propose SW#, a new CUDA graphical processor unit-enabled and memory-efficient implementation of dynamic programming algorithm, for local alignment. It can be used as either a stand-alone application or a library. Although there are other graphical processor unit implementations of the Smith–Waterman algorithm, SW# is the only one publicly available that can produce sequence alignments on genome-wide scale. For long sequences, it is at least a few hundred times faster than a CPU version of the same algorithm. Availability: Source code and installation instructions freely available for download at http://complex.zesoi.fer.hr/SW.html. Contact: mile.sikic@fer.hr Supplementary information: Supplementary results are available at Bioinformatics online. |
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