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It is a fundamental challenge that identifying disease genes from a large number of candidates for a specific disease. As the biological experiment-based methods are generally timeconsuming and laborious, it has become a new strategy to identify disease candidates by using computational approaches. In this paper, we proposed an algorithm based on the search engine ranking method, named PDGTR, to prioritize disease candidates. Firstly, we constructed a weighted human disease network by calculating the topological similarity and phenotype similarity of each pair of diseases. Then, we calculated the similarities of all the genes by using the protein-protein interaction network and the edge clustering coefficient. For a specific disease, a logistic regression model was used to generate the prior-knowledge of each gene. Finally, the search engine ranking based algorithm PDGTR was applied to prioritize the …