Function prediction for DNA-/RNA-binding proteins, GPCRs, and drug ADME-associated proteins by SVM.
Protein Pept Lett
; 15(5): 463-8, 2008.
Article
em En
| MEDLINE
| ID: mdl-18537735
ABSTRACT
This paper explores the use of support vector machine (SVM) for protein function prediction. Studies are conducted on several groups of proteins with different functions including DNA-binding proteins, RNA-binding proteins, G-protein coupled receptors, drug absorption proteins, drug metabolizing enzymes, drug distribution and excretion proteins. The computed accuracy for the prediction of these proteins is found to be in the range of 82.32% to 99.7%, which illustrates the potential of SVM in facilitating protein function prediction.
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Base de dados:
MEDLINE
Assunto principal:
Proteínas
/
Proteínas de Ligação a RNA
/
Biologia Computacional
/
Receptores Acoplados a Proteínas G
/
Proteínas de Ligação a DNA
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Protein Pept Lett
Assunto da revista:
BIOQUIMICA
Ano de publicação:
2008
Tipo de documento:
Article