Predicting enzyme class from protein structure using Bayesian classification
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.
Palabras clave
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