PreDNA: accurate prediction of DNA-binding sites in proteins by integrating sequence and geometric structure information.
Bioinformatics
; 29(6): 678-85, 2013 Mar 15.
Article
em En
| MEDLINE
| ID: mdl-23335013
ABSTRACT
MOTIVATION Protein-DNA interactions often take part in various crucial processes, which are essential for cellular function. The identification of DNA-binding sites in proteins is important for understanding the molecular mechanisms of protein-DNA interaction. Thus, we have developed an improved method to predict DNA-binding sites by integrating structural alignment algorithm and support vector machine-based methods. RESULTS:
Evaluated on a new non-redundant protein set with 224 chains, the method has 80.7% sensitivity and 82.9% specificity in the 5-fold cross-validation test. In addition, it predicts DNA-binding sites with 85.1% sensitivity and 85.3% specificity when tested on a dataset with 62 protein-DNA complexes. Compared with a recently published method, BindN+, our method predicts DNA-binding sites with a 7% better area under the receiver operating characteristic curve value when tested on the same dataset. Many important problems in cell biology require the dense non-linear interactions between functional modules be considered. Thus, our prediction method will be useful in detecting such complex interactions.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
DNA
/
Proteínas de Ligação a DNA
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Bioinformatics
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2013
Tipo de documento:
Article
País de afiliação:
China