A novel method to predict protein-protein interactions based on the information of protein-protein interaction networks and protein sequence.
Protein Pept Lett
; 18(9): 906-11, 2011 Sep.
Article
en En
| MEDLINE
| ID: mdl-21529343
Protein-protein interactions (PPIs) are crucial to most biochemical processes in human beings. Although many human PPIs have been identified by experiments, the number is still limited compared to the available protein sequences of human organisms. Recently, many computational methods have been proposed to facilitate the recognition of novel human PPIs. However the existing methods only concentrated on the information of individual PPI, while the systematic characteristic of protein-protein interaction networks (PINs) was ignored. In this study, a new method was proposed by combining the global information of PINs and protein sequence information. Random forest (RF) algorithm was implemented to develop the prediction model, and a high accuracy of 91.88% was obtained. Furthermore, the RF model was tested using three independent datasets with good performances, suggesting that our method is a useful tool for identification of PPIs and investigation into PINs as well.
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Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Algoritmos
/
Proteínas
/
Mapeo de Interacción de Proteínas
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Protein Pept Lett
Asunto de la revista:
BIOQUIMICA
Año:
2011
Tipo del documento:
Article
País de afiliación:
China
Pais de publicación:
Países Bajos