Wavelet-domain elastic net for clustering on genomes strains
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Genetics and Molecular Biology |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572018000500884 |
Resumo: | Abstract We 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. |
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Genetics and Molecular Biology |
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|
spelling |
Wavelet-domain elastic net for clustering on genomes strainsElastic netgenomeGC-contentcluster analysiswavelet transformAbstract We 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.Sociedade Brasileira de Genética2018-12-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572018000500884Genetics and Molecular Biology v.41 n.4 2018reponame:Genetics and Molecular Biologyinstname:Sociedade Brasileira de Genética (SBG)instacron:SBG10.1590/1678-4685-gmb-2018-0035info:eu-repo/semantics/openAccessFerreira,Leila MariaSáfadi,ThelmaFerreira,Juliano Linoeng2019-01-14T00:00:00Zoai:scielo:S1415-47572018000500884Revistahttp://www.gmb.org.br/ONGhttps://old.scielo.br/oai/scielo-oai.php||editor@gmb.org.br1678-46851415-4757opendoar:2019-01-14T00:00Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG)false |
dc.title.none.fl_str_mv |
Wavelet-domain elastic net for clustering on genomes strains |
title |
Wavelet-domain elastic net for clustering on genomes strains |
spellingShingle |
Wavelet-domain elastic net for clustering on genomes strains Ferreira,Leila Maria Elastic net genome GC-content cluster analysis wavelet transform |
title_short |
Wavelet-domain elastic net for clustering on genomes strains |
title_full |
Wavelet-domain elastic net for clustering on genomes strains |
title_fullStr |
Wavelet-domain elastic net for clustering on genomes strains |
title_full_unstemmed |
Wavelet-domain elastic net for clustering on genomes strains |
title_sort |
Wavelet-domain elastic net for clustering on genomes strains |
author |
Ferreira,Leila Maria |
author_facet |
Ferreira,Leila Maria Sáfadi,Thelma Ferreira,Juliano Lino |
author_role |
author |
author2 |
Sáfadi,Thelma Ferreira,Juliano Lino |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Ferreira,Leila Maria Sáfadi,Thelma Ferreira,Juliano Lino |
dc.subject.por.fl_str_mv |
Elastic net genome GC-content cluster analysis wavelet transform |
topic |
Elastic net genome GC-content cluster analysis wavelet transform |
description |
Abstract We 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. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-12-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572018000500884 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572018000500884 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1678-4685-gmb-2018-0035 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Genética |
publisher.none.fl_str_mv |
Sociedade Brasileira de Genética |
dc.source.none.fl_str_mv |
Genetics and Molecular Biology v.41 n.4 2018 reponame:Genetics and Molecular Biology instname:Sociedade Brasileira de Genética (SBG) instacron:SBG |
instname_str |
Sociedade Brasileira de Genética (SBG) |
instacron_str |
SBG |
institution |
SBG |
reponame_str |
Genetics and Molecular Biology |
collection |
Genetics and Molecular Biology |
repository.name.fl_str_mv |
Genetics and Molecular Biology - Sociedade Brasileira de Genética (SBG) |
repository.mail.fl_str_mv |
||editor@gmb.org.br |
_version_ |
1752122388869283840 |