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A data parallel strategy for aligning multiple biological sequences on multi-core computers
Faculty
Not Specified
Year:
2013
Type of Publication:
Article
Pages:
350-361
Authors:
Zhu, Xiangyuan, Li, Kenli, Salah, Ahmad
DOI:
10.1016/j.compbiomed.2012.12.009
Journal:
COMPUTERS IN BIOLOGY AND MEDICINE PERGAMON-ELSEVIER SCIENCE LTD
Volume:
43
Research Area:
Life Sciences \& Biomedicine - Other Topics; Computer Science; Engineering; Mathematical \& Computational Biology
ISSN
ISI:000316532100013
Keywords :
Data parallelism, Parallel algorithm, Multi-core, Multiple sequence alignment, Biological sequences, Clustering
Abstract:
In this paper, we address the large-scale biological sequence alignment problem, which has an increasing demand in computational biology. We employ data parallelism paradigm that is suitable for handling large-scale processing on multi-core computers to achieve a high degree of parallelism. Using the data parallelism paradigm, we propose a general strategy which can be used to speed up any multiple sequence alignment method. We applied five different clustering algorithms in our strategy and implemented rigorous tests on an 8-core computer using four traditional benchmarks and artificially generated sequences. The results show that our multi-core-based implementations can achieve up to 151-fold improvements in execution time while losing 2.19\% accuracy on average. The source code of the proposed strategy, together with the test sets used in our analysis, is available on request. (c) 2013 Elsevier Ltd. All rights reserved.
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