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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

HAMSA: Highly Accelerated Multiple Sequence Aligner

Author 1: Naglaa M. Reda
Author 2: Mohammed Al-Neama
Author 3: Fayed F. M. Ghaleb

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2016.070661

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 6, 2016.

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Abstract: For biologists, the existence of an efficient tool for multiple sequence alignment is essential. This work presents a new parallel aligner called HAMSA. HAMSA is a bioinformatics application designed for highly accelerated alignment of multiple sequences of proteins and DNA/RNA on a multi-core cluster system. The design of HAMSA is based on a combination of our new optimized algorithms proposed recently of vectorization, partitioning, and scheduling. It mainly operates on a distance vector instead of a distance matrix. It accomplishes similarity computations and generates the guide tree in a highly accelerated and accurate manner. HAMSA outperforms MSAProbs with 21.9- fold speedup, and ClustalW-MPI of 11-fold speedup. It can be considered as an essential tool for structure prediction, protein classification, motive finding and drug design studies

Keywords: Bioinformatics; Multiple sequence alignment; parallel programming; Clusters; Multi-cores

Naglaa M. Reda, Mohammed Al-Neama and Fayed F. M. Ghaleb, “HAMSA: Highly Accelerated Multiple Sequence Aligner” International Journal of Advanced Computer Science and Applications(IJACSA), 7(6), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070661

@article{Reda2016,
title = {HAMSA: Highly Accelerated Multiple Sequence Aligner},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070661},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070661},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {6},
author = {Naglaa M. Reda and Mohammed Al-Neama and Fayed F. M. Ghaleb}
}


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