GO Semantic Similarity-Based False Positive Reduction of Protein-Protein Interactions

The prediction of protein interaction is one of the most important issues in post-genomic era. However, false positive predictions cannot be avoid in both of experimental methods and computational approaches, therefore false positive reduction is a fundamental step to generate high reliable protein interactions. In this paper, we calculated the similarity of proteins by the semantic similarity of gene ontology (GO) terms which belonged to the associated proteins. Filtering algorithm is proposed based on the similarity of proteins which was used to filter the false positive predictions. The experimental results show that the proposed filtering method can decrease the false positive effectively which has enhanced the accuracy of the protein-protein interaction prediction.