Predicting enzyme class from protein structure using Bayesian classification
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.
Full text:
Available
Index:
LILACS (Americas)
Main subject:
Protein Conformation
/
Bayes Theorem
/
Enzymes
Type of study:
Prognostic study
/
Risk factors
Limits:
Humans
Language:
English
Journal:
Genet. mol. res. (Online)
Journal subject:
Molecular Biology
/
Genetics
Year:
2006
Type:
Article
Affiliation country:
Brazil
Institution/Affiliation country:
Embrapa Information Technology/BR
Similar
MEDLINE
...
LILACS
LIS