Next-generation bioinformatics: using many-core processor architecture to develop a web service for sequence alignment

Motivation: Bioinformatics algorithms and computing power are the main bottlenecks for analyzing huge amount of data generated by the current technologies, such as the ‘next-generation’ sequencing methodologies. At the same time, most powerful microprocessors are based on many-core chips, yet most a...

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Vydané v:Bioinformatics Ročník 26; číslo 5; s. 683 - 686
Hlavní autori: Gálvez, Sergio, Díaz, David, Hernández, Pilar, Esteban, Francisco J., Caballero, Juan A., Dorado, Gabriel
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Oxford Oxford University Press 01.03.2010
Predmet:
Algorithms
Alignment
Bioinformatics
Biological and medical sciences
Computation
Computational Biology - methods
Fundamental and applied biological sciences. Psychology
General aspects
Internet
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Microprocessors
On-line systems
Parallel processing
Personal computers
Sequence Alignment - methods
Cores
Architecture
Bioinformatics
Sequence alignment
World wide web
Web service
ISSN:1367-4803, 1367-4811, 1460-2059, 1367-4811
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Shrnutí:Motivation: Bioinformatics algorithms and computing power are the main bottlenecks for analyzing huge amount of data generated by the current technologies, such as the ‘next-generation’ sequencing methodologies. At the same time, most powerful microprocessors are based on many-core chips, yet most applications cannot exploit such power, requiring parallelized algorithms. As an example of next-generation bioinformatics, we have developed from scratch a new parallelization of the Needleman–Wunsch (NW) sequence alignment algorithm for the 64-core Tile64 microprocessor. The unprecedented performance it offers for a standalone personal computer (PC) is discussed, optimally aligning sequences up to 20 times faster than the non-parallelized version, thus saving valuable time. Availability: This algorithm is available as a free web service for the scientific community at http://www.sicuma.uma.es/multicore. The open source code is also available on such site. Contact: galvez@uma.es Supplementary information: Supplementary data are available at Bioinformatics online.
Bibliografia:ark:/67375/HXZ-R4MXKKRT-J
Associate Editor: Dmitrij Frishman
ArticleID:btq017
To whom correspondence should be addressed.
istex:7A9136B0C66659AB5DD0040039DFBB84C2EBC54B
ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 23
ISSN:1367-4803
1367-4811
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btq017