Predicting enzyme class from protein structure using Bayesian classification.
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.
Borro
Luiz C
LC
Embrapa Information Technology, André Tosello, 209, Caixa Postal 6041, 13083-886 Campinas, SP, Brazil.
Oliveira
Stanley R M
SR
Yamagishi
Michel E B
ME
Mancini
Adaulto L
AL
Jardine
José G
JG
Mazoni
Ivan
I
Santos
Edgard H dos
EH
Higa
Roberto H
RH
Kuser
Paula R
PR
Neshich
Goran
G
D000465:Algorithms; D001499:Bayes Theorem; D004798:Enzymes / Q000737:chemistry* / Q000145:classification*; D006801:Humans; D011487:Protein Conformation; D016415:Sequence Alignment
D004798:Enzymes