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dc.contributor.authorFERREIRA, L. M.pt_BR
dc.contributor.authorSÁFADI, T.pt_BR
dc.contributor.authorFERREIRA, J. L.pt_BR
dc.date.accessioned2019-06-19T01:16:02Z-
dc.date.available2019-06-19T01:16:02Z-
dc.date.created2019-06-18
dc.date.issued2018
dc.identifier.citationGenetics and Molecular Biology, v. 41, n. 4, p. 884-892, Oct./Dec. 2018.pt_BR
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1109931-
dc.descriptionWe propose to evaluate genome similarity by combining discrete non-decimated wavelet transform (NDWT) and elastic net. The wavelets represent a signal with levels of detail, that is, hidden components are detected by means of the decomposition of this signal, where each level provides a different characteristic. The main feature of the elastic net is the grouping of correlated variables where the number of predictors is greater than the number of observations. The combination of these two methodologies applied in the clustering analysis of the Mycobacterium tuberculosis genome strains proved very effective, being able to identify clusters at each level of decomposition.pt_BR
dc.language.isoporpt_BR
dc.rightsopenAccesspt_BR
dc.titleWavelet-domain elastic net for clustering on genomes strains.pt_BR
dc.typeArtigo de periódicopt_BR
dc.date.updated2019-12-16T11:11:11Z
dc.subject.thesagroGenomapt_BR
dc.subject.thesagroMicobactériapt_BR
dc.subject.thesagroBactéria Patogênicapt_BR
dc.subject.thesagroLinhagempt_BR
dc.subject.thesagroGenéticapt_BR
dc.subject.thesagroAnálise Estatísticapt_BR
riaa.ainfo.id1109931pt_BR
riaa.ainfo.lastupdate2019-12-16 -02:00:00
dc.contributor.institutionLeila Maria Ferreira, UFLA; Thelma Sáfadi, UFLA; JULIANO LINO FERREIRA, CPPSUL.pt_BR
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