Predicting enzyme class from protein structure using Bayesian classification.

Detalhes bibliográficos
Autor(a) principal: BORRO, L. C.
Data de Publicação: 2006
Outros Autores: OLIVEIRA, S. R. M., YAMAGISHI, M. E. B., MANCINI, A. L., JARDINE, J. G., MAZONI, I., SANTOS, E. H. dos, HIGA, R. H., KUSER, P. R., NESHICH, G.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
Texto Completo: http://www.alice.cnptia.embrapa.br/alice/handle/doc/9196
Resumo: ABSTRACT. Predicting enzyme class from protein structure parameters is a challenging problem in protein analysis. We developed a method to predict enzyme class that combines the strengths of statistical and data-mining methods. This method has a strong mathematical foundation and is simple to implement, achieving an accuracy of 45%. A comparison with the methods found in the literature designed to predict enzyme class showed that our method outperforms the existing methods.
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spelling Predicting enzyme class from protein structure using Bayesian classification.BioinformáticaEstrutura de proteínaClasse de enzimaBayesian classificationProtein function predictionNaive BayesEnzyme classification numberBayesian classifierData classificationBioinformaticsProtein structureABSTRACT. Predicting enzyme class from protein structure parameters is a challenging problem in protein analysis. We developed a method to predict enzyme class that combines the strengths of statistical and data-mining methods. This method has a strong mathematical foundation and is simple to implement, achieving an accuracy of 45%. A comparison with the methods found in the literature designed to predict enzyme class showed that our method outperforms the existing methods.LUIZ C. BORRO, CNPTIA; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; MICHEL EDUARDO BELEZA YAMAGISHI, CNPTIA; ADAUTO LUIZ MANCINI, CNPTIA; JOSE GILBERTO JARDINE, CNPTIA; IVAN MAZONI, CNPTIA; EDGARD HENRIQUE DOS SANTOS, CNPTIA; ROBERTO HIROSHI HIGA, CNPTIA; PAULA REGINA KUSER FALCAO, CNPTIA; GORAN NESHICH, CNPTIA.BORRO, L. C.OLIVEIRA, S. R. M.YAMAGISHI, M. E. B.MANCINI, A. L.JARDINE, J. G.MAZONI, I.SANTOS, E. H. dosHIGA, R. H.KUSER, P. R.NESHICH, G.2011-04-10T11:11:11Z2011-04-10T11:11:11Z2007-03-0720062017-05-17T11:11:11Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleGenetics and Molecular Research, v. 5, n. 1, p. 193-202, 2006.http://www.alice.cnptia.embrapa.br/alice/handle/doc/9196enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2017-05-18T01:24:58Zoai:www.alice.cnptia.embrapa.br:doc/9196Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542017-05-18T01:24:58falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542017-05-18T01:24:58Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false
dc.title.none.fl_str_mv Predicting enzyme class from protein structure using Bayesian classification.
title Predicting enzyme class from protein structure using Bayesian classification.
spellingShingle Predicting enzyme class from protein structure using Bayesian classification.
BORRO, L. C.
Bioinformática
Estrutura de proteína
Classe de enzima
Bayesian classification
Protein function prediction
Naive Bayes
Enzyme classification number
Bayesian classifier
Data classification
Bioinformatics
Protein structure
title_short Predicting enzyme class from protein structure using Bayesian classification.
title_full Predicting enzyme class from protein structure using Bayesian classification.
title_fullStr Predicting enzyme class from protein structure using Bayesian classification.
title_full_unstemmed Predicting enzyme class from protein structure using Bayesian classification.
title_sort Predicting enzyme class from protein structure using Bayesian classification.
author BORRO, L. C.
author_facet BORRO, L. C.
OLIVEIRA, S. R. M.
YAMAGISHI, M. E. B.
MANCINI, A. L.
JARDINE, J. G.
MAZONI, I.
SANTOS, E. H. dos
HIGA, R. H.
KUSER, P. R.
NESHICH, G.
author_role author
author2 OLIVEIRA, S. R. M.
YAMAGISHI, M. E. B.
MANCINI, A. L.
JARDINE, J. G.
MAZONI, I.
SANTOS, E. H. dos
HIGA, R. H.
KUSER, P. R.
NESHICH, G.
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv LUIZ C. BORRO, CNPTIA; STANLEY ROBSON DE MEDEIROS OLIVEIRA, CNPTIA; MICHEL EDUARDO BELEZA YAMAGISHI, CNPTIA; ADAUTO LUIZ MANCINI, CNPTIA; JOSE GILBERTO JARDINE, CNPTIA; IVAN MAZONI, CNPTIA; EDGARD HENRIQUE DOS SANTOS, CNPTIA; ROBERTO HIROSHI HIGA, CNPTIA; PAULA REGINA KUSER FALCAO, CNPTIA; GORAN NESHICH, CNPTIA.
dc.contributor.author.fl_str_mv BORRO, L. C.
OLIVEIRA, S. R. M.
YAMAGISHI, M. E. B.
MANCINI, A. L.
JARDINE, J. G.
MAZONI, I.
SANTOS, E. H. dos
HIGA, R. H.
KUSER, P. R.
NESHICH, G.
dc.subject.por.fl_str_mv Bioinformática
Estrutura de proteína
Classe de enzima
Bayesian classification
Protein function prediction
Naive Bayes
Enzyme classification number
Bayesian classifier
Data classification
Bioinformatics
Protein structure
topic Bioinformática
Estrutura de proteína
Classe de enzima
Bayesian classification
Protein function prediction
Naive Bayes
Enzyme classification number
Bayesian classifier
Data classification
Bioinformatics
Protein structure
description ABSTRACT. Predicting enzyme class from protein structure parameters is a challenging problem in protein analysis. We developed a method to predict enzyme class that combines the strengths of statistical and data-mining methods. This method has a strong mathematical foundation and is simple to implement, achieving an accuracy of 45%. A comparison with the methods found in the literature designed to predict enzyme class showed that our method outperforms the existing methods.
publishDate 2006
dc.date.none.fl_str_mv 2006
2007-03-07
2011-04-10T11:11:11Z
2011-04-10T11:11:11Z
2017-05-17T11:11:11Z
dc.type.driver.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Genetics and Molecular Research, v. 5, n. 1, p. 193-202, 2006.
http://www.alice.cnptia.embrapa.br/alice/handle/doc/9196
identifier_str_mv Genetics and Molecular Research, v. 5, n. 1, p. 193-202, 2006.
url http://www.alice.cnptia.embrapa.br/alice/handle/doc/9196
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron:EMBRAPA
instname_str Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
instacron_str EMBRAPA
institution EMBRAPA
reponame_str Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
collection Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)
repository.name.fl_str_mv Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)
repository.mail.fl_str_mv cg-riaa@embrapa.br
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