dc.creatorGalves, M
dc.creatorQuitzau, JAA
dc.creatorDias, Z
dc.date2006
dc.date2014-11-10T17:03:47Z
dc.date2015-11-26T18:07:03Z
dc.date2014-11-10T17:03:47Z
dc.date2015-11-26T18:07:03Z
dc.date.accessioned2018-03-29T00:49:11Z
dc.date.available2018-03-29T00:49:11Z
dc.identifierGenetics And Molecular Research. Funpec-editora, v. 5, n. 1, n. 143, n. 153, 2006.
dc.identifier1676-5680
dc.identifierWOS:000203011700020
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/61896
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/61896
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/61896
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1293493
dc.descriptionA great effort has been made to identify and map a large set of single nucleotide polymorphisms. The goal is to determine human DNA variants that contribute most significantly to population variation in each trait. Different algorithms and software packages, such as PolyBayes and PolyPhred, have been developed to address this problem. We present strategies to detect single nucleotide polymorphisms, using chromatogram analysis and consensi of multiple aligned sequences. The algorithms were tested using HIV datasets, and the results were compared with those produced by PolyBayes and PolyPhred using the same dataset. Our algorithms produced significantly better results than these two software packages.
dc.description5
dc.description1
dc.description143
dc.description153
dc.languageen
dc.publisherFunpec-editora
dc.publisherRibeirao Preto
dc.publisherBrasil
dc.relationGenetics And Molecular Research
dc.relationGenet. Mol. Res.
dc.rightsfechado
dc.sourceWeb of Science
dc.subjectsingle nucleotide polymorphism
dc.subjectchromatogram
dc.subjectalgorithm
dc.subjectbase-calling analysis
dc.subjectsequence alignment
dc.subjectHIV
dc.titleNew strategy to detect single nucleotide polymorphisms
dc.typeArtículos de revistas


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