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Improving multiple sequence alignment biological accuracy through genetic algorithms

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dc.creator Orobitg Cortada, Miquel
dc.creator Cores Prado, Fernando
dc.creator Guirado Fernández, Fernando
dc.creator Roig Mateu, Concepció
dc.creator Notredame, Cedric
dc.date 2013
dc.date.accessioned 2025-11-03T12:14:48Z
dc.date.available 2025-11-03T12:14:48Z
dc.identifier https://doi.org/10.1007/s11227-012-0856-9
dc.identifier 0920-8542
dc.identifier http://hdl.handle.net/10459.1/58496
dc.identifier.uri http://fima-docencia.ub.edu:8080/xmlui/handle/123456789/23842
dc.description 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.
dc.description This work was supported by the Ministry of Education and Science of Spain under contract TIN2011-28689-C02-02, TIN2010-12011-E and Consolider CSD2007-00050. MO is funded by the CUR of DIUE of GENCAT. CN is funded by the Plan Nacional BFU2008-00419 and the 7th Framework Programme of the European Commission through the LEISHDRUG project (no. 223414) and The Quantomics project (KBBE-2A-222664).
dc.language eng
dc.publisher Springer
dc.relation MICINN/PN2008-2011/TIN2011-28689-C02-02
dc.relation MICINN/PN2008-2011/TIN2010-12011-E
dc.relation MICINN/PN2008-2011/BFU2008-00419
dc.relation Reproducció del document publicat a https://doi.org/10.1007/s11227-012-0856-9
dc.relation The Journal of Supercomputing, 2013, vol. 65, núm. 3, p. 1076-1088
dc.relation info:eu-repo/grantAgreement/EC/FP7/223414
dc.relation info:eu-repo/grantAgreement/EC/FP7/222664
dc.rights (c) Springer Science and Business Media New York, 2013
dc.rights info:eu-repo/semantics/restrictedAccess
dc.subject MSA
dc.subject Evaluation
dc.subject Genetic algorithm
dc.title Improving multiple sequence alignment biological accuracy through genetic algorithms
dc.type article
dc.type publishedVersion


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