Improving multiple sequence alignment biological accuracy through genetic algorithms

Orobitg Cortada, Miquel; Cores Prado, Fernando; Guirado Fernández, Fernando; Roig Mateu, Concepció; Notredame, Cedric

doi:https://doi.org/10.1007/s11227-012-0856-9

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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.

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