title: Construction of ontology augmented networks for protein complex prediction.
abstract: 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.
authors: College of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, China. zhyj@dlut.edu.cn
authors: Yijia
authors: Y
authors: Zhang
authors: Hongfei
authors: H
authors: Lin
authors: Zhihao
authors: Z
authors: Yang
authors: Jian
authors: J
authors: Wang
mesh_terms: D000465:Algorithms; D030562:Databases, Protein; D008954:Models, Biological; D058977:Molecular Sequence Annotation / Q000379:methods; D046912:Multiprotein Complexes; D025941:Protein Interaction Mapping; D060066:Protein Interaction Maps
chemical_list: D046912:Multiprotein Complexes
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