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Estimating evolutionary distances between genomic sequences from spaced-word matches.
Morgenstern, Burkhard; Zhu, Bingyao; Horwege, Sebastian; Leimeister, Chris André.
Afiliação
  • Morgenstern B; University of Göttingen, Department of Bioinformatics, Goldschmidtstr. 1, Göttingen, 37073 Germany ; Université d'Evry Val d'Essonne, Laboratoire Statistique et Génome, UMR CNRS 8071, USC INRA 23 Boulevard de France, Evry, 91037 France.
  • Zhu B; University of Göttingen, Department of General Microbiology, Grisebachstr. 8, Göttingen, 37073 Germany.
  • Horwege S; University of Göttingen, Department of Bioinformatics, Goldschmidtstr. 1, Göttingen, 37073 Germany.
  • Leimeister CA; University of Göttingen, Department of Bioinformatics, Goldschmidtstr. 1, Göttingen, 37073 Germany.
Algorithms Mol Biol ; 10: 5, 2015.
Article em En | MEDLINE | ID: mdl-25685176
ABSTRACT
Alignment-free methods are increasingly used to calculate evolutionary distances between DNA and protein sequences as a basis of phylogeny reconstruction. Most of these methods, however, use heuristic distance functions that are not based on any explicit model of molecular evolution. Herein, we propose a simple estimator d N of the evolutionary distance between two DNA sequences that is calculated from the number N of (spaced) word matches between them. We show that this distance function is more accurate than other distance measures that are used by alignment-free methods. In addition, we calculate the variance of the normalized number N of (spaced) word matches. We show that the variance of N is smaller for spaced words than for contiguous words, and that the variance is further reduced if our spaced-words approach is used with multiple patterns of 'match positions' and 'don't care positions'. Our software is available online and as downloadable source code at http//spaced.gobics.de/.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2015 Tipo de documento: Article