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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
Suggested citation
Orobitg Cortada, Miquel; Cores Prado, Fernando; Guirado Fernández, Fernando; Roig Mateu, Concepció; Notredame, Cedric; . (2013) . Improving multiple sequence alignment biological accuracy through genetic algorithms. The Journal of Supercomputing, 2013, vol. 65, núm. 3, p. 1076-1088. https://doi.org/10.1007/s11227-012-0856-9.
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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
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The Journal of Supercomputing, 2013, vol. 65, núm. 3, p. 1076-1088
European research projects
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  • Publicacions de projectes de recerca del Plan Nacional [2948]
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