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Overestimation for Multiple Sequence Alignment

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1 Author(s)
Tristan Cazenave ; L.I.A.S.D., Dept. Informatique, Université Paris 8. cazenave@ai.univ-paris8.fr

Multiple sequence alignment is an important problem in computational biology. A-star is an algorithm that can be used to find exact alignments. We present a simple modification of the A-star algorithm that improves much multiple sequence alignment, both in time and memory, at the cost of a small accuracy loss. It consists in overestimating the admissible heuristic. A typical speedup for random sequences of length two hundred fifty is 47 associated to a memory gain of 13 with an error rate of 0.09%. Concerning real sequences, the speedup can be greater than 20,000 and the memory gain greater than 150, the error rate being in the range from 0.08% to 0.67% for the sequences we have tested. Overestimation can align sequences that are not possible to align with the exact algorithm

Published in:

Computational Intelligence and Bioinformatics and Computational Biology, 2007. CIBCB '07. IEEE Symposium on

Date of Conference:

1-5 April 2007