Wavelet-domain elastic net for clustering on genomes strains.

Wavelet-domain elastic net for clustering on genomes strains.

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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Bibliographic Details
Main Authors: FERREIRA, L. M., SÁFADI, T., FERREIRA, J. L.
Other Authors: Leila Maria Ferreira, UFLA; Thelma Sáfadi, UFLA; JULIANO LINO FERREIRA, CPPSUL.
Format: Artigo de periódico biblioteca
Language:pt_BR
pt_BR
Published: 2019-06-18
Subjects:Genoma, Micobactéria, Bactéria Patogênica, Linhagem, Genética, Análise Estatística,
Online Access:http://www.alice.cnptia.embrapa.br/alice/handle/doc/1109931
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spelling dig-alice-doc-11099312019-06-19T01:16:09Z Wavelet-domain elastic net for clustering on genomes strains. FERREIRA, L. M. SÁFADI, T. FERREIRA, J. L. Leila Maria Ferreira, UFLA; Thelma Sáfadi, UFLA; JULIANO LINO FERREIRA, CPPSUL. Genoma Micobactéria Bactéria Patogênica Linhagem Genética Análise Estatística 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. 2019-06-19T01:16:02Z 2019-06-19T01:16:02Z 2019-06-18 2018 2019-12-16T11:11:11Z Artigo de periódico Genetics and Molecular Biology, v. 41, n. 4, p. 884-892, Oct./Dec. 2018. http://www.alice.cnptia.embrapa.br/alice/handle/doc/1109931 pt_BR pt_BR openAccess
institution EMBRAPA
collection DSpace
country Brasil
countrycode BR
component Bibliográfico
access En linea
databasecode dig-alice
tag biblioteca
region America del Sur
libraryname Sistema de bibliotecas de EMBRAPA
language pt_BR
pt_BR
topic Genoma
Micobactéria
Bactéria Patogênica
Linhagem
Genética
Análise Estatística
Genoma
Micobactéria
Bactéria Patogênica
Linhagem
Genética
Análise Estatística
spellingShingle Genoma
Micobactéria
Bactéria Patogênica
Linhagem
Genética
Análise Estatística
Genoma
Micobactéria
Bactéria Patogênica
Linhagem
Genética
Análise Estatística
FERREIRA, L. M.
SÁFADI, T.
FERREIRA, J. L.
Wavelet-domain elastic net for clustering on genomes strains.
description 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.
author2 Leila Maria Ferreira, UFLA; Thelma Sáfadi, UFLA; JULIANO LINO FERREIRA, CPPSUL.
author_facet Leila Maria Ferreira, UFLA; Thelma Sáfadi, UFLA; JULIANO LINO FERREIRA, CPPSUL.
FERREIRA, L. M.
SÁFADI, T.
FERREIRA, J. L.
format Artigo de periódico
topic_facet Genoma
Micobactéria
Bactéria Patogênica
Linhagem
Genética
Análise Estatística
author FERREIRA, L. M.
SÁFADI, T.
FERREIRA, J. L.
author_sort FERREIRA, L. M.
title Wavelet-domain elastic net for clustering on genomes strains.
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.
publishDate 2019-06-18
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/1109931
work_keys_str_mv AT ferreiralm waveletdomainelasticnetforclusteringongenomesstrains
AT safadit waveletdomainelasticnetforclusteringongenomesstrains
AT ferreirajl waveletdomainelasticnetforclusteringongenomesstrains
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