Using support vector machines for prediction of protein structural classes based on discrete wavelet transform.
J Comput Chem
; 30(8): 1344-50, 2009 Jun.
Article
em En
| MEDLINE
| ID: mdl-19009604
ABSTRACT
The prediction of secondary structure is a fundamental and important component in the analytical study of protein structure and functions. How to improve the predictive accuracy of protein structural classification by effectively incorporating the sequence-order effects is an important and challenging problem. In this study, a new method, in which the support vector machine combines with discrete wavelet transform, is developed to predict the protein structural classes. Its performance is assessed by cross-validation tests. The predicted results show that the proposed approach can remarkably improve the success rates, and might become a useful tool for predicting the other attributes of proteins as well.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Proteínas
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
J Comput Chem
Assunto da revista:
QUIMICA
Ano de publicação:
2009
Tipo de documento:
Article