Construction of Ontology Augmented Networks for Protein Complex PredictionReportar como inadecuado




Construction of Ontology Augmented Networks for Protein Complex Prediction - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

Protein complexes are of great importance in understanding the principles of cellular organization and function. The increase in available protein-protein interaction data, gene ontology and other resources make it possible to develop computational methods for protein complex prediction. Most existing methods focus mainly on the topological structure of protein-protein interaction networks, and largely ignore the gene ontology annotation information. In this article, we constructed ontology augmented networks with protein-protein interaction data and gene ontology, which effectively unified the topological structure of protein-protein interaction networks and the similarity of gene ontology annotations into unified distance measures. After constructing ontology augmented networks, a novel method clustering based on ontology augmented networks was proposed to predict protein complexes, which was capable of taking into account the topological structure of the protein-protein interaction network, as well as the similarity of gene ontology annotations. Our method was applied to two different yeast protein-protein interaction datasets and predicted many well-known complexes. The experimental results showed that i ontology augmented networks and the unified distance measure can effectively combine the structure closeness and gene ontology annotation similarity; ii our method is valuable in predicting protein complexes and has higher F1 and accuracy compared to other competing methods.



Autor: Yijia Zhang , Hongfei Lin, Zhihao Yang, Jian Wang

Fuente: http://plos.srce.hr/



DESCARGAR PDF




Documentos relacionados