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Predicting enzyme class from protein structure using Bayesian classification
Borro, L. C; Oliveira, S. R; Yamagishi, M. E; Mancini, A. L; Jardine, J. G; Mazoni, I; Santos, E. H; Higa, R. H; Kuser, P. R; Neshich, G.
Afiliación
  • Borro, L. C; Embrapa Information Technology. Campinas. BR
  • Oliveira, S. R; Embrapa Information Technology. Campinas. BR
  • Yamagishi, M. E; Embrapa Information Technology. Campinas. BR
  • Mancini, A. L; Embrapa Information Technology. Campinas. BR
  • Jardine, J. G; Embrapa Information Technology. Campinas. BR
  • Mazoni, I; Embrapa Information Technology. Campinas. BR
  • Santos, E. H; Embrapa Information Technology. Campinas. BR
  • Higa, R. H; Embrapa Information Technology. Campinas. BR
  • Kuser, P. R; Embrapa Information Technology. Campinas. BR
  • Neshich, G; Embrapa Information Technology. Campinas. BR
Genet. mol. res. (Online) ; Genet. mol. res. (Online);5(1): 193-202, Mar. 31, 2006. graf, tab
Article en En | LILACS | ID: lil-449133
Biblioteca responsable: BR1.1
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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Texto completo: 1 Índice: LILACS Asunto principal: Conformación Proteica / Teorema de Bayes / Enzimas Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Genet. mol. res. (Online) Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2006 Tipo del documento: Article
Texto completo: 1 Índice: LILACS Asunto principal: Conformación Proteica / Teorema de Bayes / Enzimas Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Genet. mol. res. (Online) Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2006 Tipo del documento: Article