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Erschienen in:
01.09.2013
Improving multiple sequence alignment biological accuracy through genetic algorithms
Erschienen in: The Journal of Supercomputing | Ausgabe 3/2013
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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.