Heterogeneous network-based propagation algorithm for discovering bladder cancer-related genes

Bladder cancer (BC) is a global fatal malignancy, which results in 114,000 deaths in 1990 and even 170,000 deaths in 2010 [1]. Therefore, the identification of BC-related genes is in emergency need for analyzing BC more comprehensively. In this study, we propose a heterogeneous network-based propagation algorithm using multi-dimensional data to score and rank the candidate BC-related genes. The novelty of the algorithm lies in that the propagation takes full advantage of the comprehensive information in the heterogeneous network and the added resistance properly reduces the impact of hubs in the network. The results of performance evaluation indicate that the proposed method significantly exceed the network model based method with single-dimensional data and another existing method.