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The Gene Ontology (GO) was widely used to annotate gene products, which provide a new way to analyze the relationship between the gene products. Many approaches based on GO were proposed to measure the functional similarity of gene products. In order to improve the accuracy, we proposed a novel method, MUI, to measure functional similarity of gene products combining the information of the interactions between the GO terms and the semantic similarity measures based on the information content. The dataset from OMIM database was used to evaluate these functional similarity measures including MUI, Max, Mean, and Schlicker method. The receiver operating characteristic (ROC) curve illustrated that MUI outperformed the other methods with lower false positive rate and false negative rate.