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Multiple Sequence Alignments with Regular Expression Constraints on a Cloud Service System

Multiple Sequence Alignments with Regular Expression Constraints on a Cloud Service System

Yu-Shiang Lin, Chun-Yuan Lin, Hsiao-Chieh Chi, Yeh-Ching Chung
Copyright: © 2013 |Volume: 5 |Issue: 3 |Pages: 10
ISSN: 1938-0259|EISSN: 1938-0267|EISBN13: 9781466634367|DOI: 10.4018/jghpc.2013070105
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MLA

Lin, Yu-Shiang, et al. "Multiple Sequence Alignments with Regular Expression Constraints on a Cloud Service System." IJGHPC vol.5, no.3 2013: pp.55-64. http://doi.org/10.4018/jghpc.2013070105

APA

Lin, Y., Lin, C., Chi, H., & Chung, Y. (2013). Multiple Sequence Alignments with Regular Expression Constraints on a Cloud Service System. International Journal of Grid and High Performance Computing (IJGHPC), 5(3), 55-64. http://doi.org/10.4018/jghpc.2013070105

Chicago

Lin, Yu-Shiang, et al. "Multiple Sequence Alignments with Regular Expression Constraints on a Cloud Service System," International Journal of Grid and High Performance Computing (IJGHPC) 5, no.3: 55-64. http://doi.org/10.4018/jghpc.2013070105

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Abstract

Multiple sequence alignments with constraints are of priority concern in computational biology. Constrained sequence alignment incorporates the domain knowledge of biologists into sequence alignments such that the user-specified residues/segments are aligned together according to the alignment results. A series of constrained multiple sequence alignment tools have been developed in relevant literatures in the recent decade. GPU-REMuSiC is the most advanced method with the regular expression constraints, in which graphics processing units (GPUs) with CUDA are used. GPU-REMuSiC can achieve a speedup ratio of 29x for overall computation time based on the experimental results. However, the execution environment of GPU-REMuSiC must be constructed; it is a threshold for biologists to set up it. Therefore, this work presents an intuitive friendly user interface of GPU-REMuSiC for the potential cloud server with GPUs, called Cloud GPU-REMuSiC. Implementing the user interface via a network allows us to transmit the input data to a remote server without a complex cumbersome setting in a local host. Finally, the alignment results can be obtained from a remote cloud server with GPUs. Cloud GPU-REMuSiC is highly promising as an online application that is accessible without time or location constraints.

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