Improving multiple sequence alignment biological accuracy through genetic algorithms

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Issue date
2013
Author
Orobitg Cortada, Miquel
Cores Prado, Fernando
Guirado Fernández, Fernando
Roig Mateu, Concepció
Notredame, Cedric
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Abstract
Accuracy on multiple sequence alignments (MSA) is of great significance for such important biological applications as evolution and phylogenetic analysis, homology and domain structure prediction. In such analyses, alignment accuracy is crucial. In this paper, we investigate a combined scoring function
capable of obtaining a good approximation to the biological quality of the alignment. The algorithm uses the information obtained by the different quality scores in order to improve the accuracy. The results show that the combined score is able to evaluate alignments better than the isolated scores.
URI
http://hdl.handle.net/10459.1/58496
DOI
https://doi.org/10.1007/s11227-012-0856-9
Is part of
The Journal of Supercomputing, 2013, vol. 65, núm. 3, p. 1076-1088
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