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Genet. mol. res. (Online) ; 5(1): 193-202, Mar. 31, 2006. graf, tab
Article in English | LILACS | ID: lil-449133

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.


Subject(s)
Humans , Protein Conformation , Enzymes/chemistry , Enzymes/classification , Bayes Theorem , Algorithms , Sequence Alignment
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