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Faster Algorithms for Optimal Multiple Sequence Alignment Based on Pairwise Comparisons
October-December 2006 (vol. 3 no. 4)
pp. 408-422
ASCII Text
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Yonatan Bilu, Pankaj K. Agarwal, Rachel Kolodny, "Faster Algorithms for Optimal Multiple Sequence Alignment Based on Pairwise Comparisons," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 3, no. 4, pp. 408-422, October-December, 2006.
 
 
BibTex
x
 
@article{ 10.1109/TCBB.2006.53,
author = {Yonatan Bilu and Pankaj K. Agarwal and Rachel Kolodny},
title = {Faster Algorithms for Optimal Multiple Sequence Alignment Based on Pairwise Comparisons},
journal ={IEEE/ACM Transactions on Computational Biology and Bioinformatics},
volume = {3},
number = {4},
issn = {1545-5963},
year = {2006},
pages = {408-422},
doi = {http://doi.ieeecomputersociety.org/10.1109/TCBB.2006.53},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE/ACM Transactions on Computational Biology and Bioinformatics
TI - Faster Algorithms for Optimal Multiple Sequence Alignment Based on Pairwise Comparisons
IS - 4
SN - 1545-5963
SP408
EP422
EPD - 408-422
A1 - Yonatan Bilu,
A1 - Pankaj K. Agarwal,
A1 - Rachel Kolodny,
PY - 2006
KW - Multiple Sequence Alignment
KW - algorithms
KW - dynamic programming
KW - shortest path.
VL - 3
JA - IEEE/ACM Transactions on Computational Biology and Bioinformatics
ER -
 
Multiple Sequence Alignment (MSA) is one of the most fundamental problems in computational molecular biology. The running time of the best known scheme for finding an optimal alignment, based on dynamic programming, increases exponentially with the number of input sequences. Hence, many heuristics were suggested for the problem. We consider a version of the MSA problem where the goal is to find an optimal alignment in which matches are restricted to positions in predefined matching segments. We present several techniques for making the dynamic programming algorithm more efficient, while still finding an optimal solution under these restrictions. We prove that it suffices to find an optimal alignment of the predefined sequence segments, rather than single letters, thereby reducing the input size and thus improving the running time. We also identify "shortcuts” that expedite the dynamic programming scheme. Empirical study shows that, taken together, these observations lead to an improved running time over the basic dynamic programming algorithm by 4 to 12 orders of magnitude, while still obtaining an optimal solution. Under the additional assumption that matches between segments are transitive, we further improve the running time for finding the optimal solution by restricting the search space of the dynamic programming algorithm.

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Index Terms:
Multiple Sequence Alignment, algorithms, dynamic programming, shortest path.
Citation:
Yonatan Bilu, Pankaj K. Agarwal, Rachel Kolodny, "Faster Algorithms for Optimal Multiple Sequence Alignment Based on Pairwise Comparisons," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 3, no. 4, pp. 408-422, Oct.-Dec. 2006, doi:10.1109/TCBB.2006.53
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