A Bipartite Network Module-Based Project to Predict Pathogen–Host Association - Li, Jie; Wang, Shiming; Chen, Zhuo; Wang, Yadong (Frontiers in Genetics, 2020)
Pathogen-host interaction play an important role in understanding the mechanism by which a pathogen can infect its host. Some approaches to predict pathogen-host association are developed, however prediction accuracy is still lower. In the paper, we proposed a bipartite network module-based approach to improve prediction accuracy. First, a bipartite network with pathogens and hosts is constructed. Next, pathogens and hosts are divided into different modules respectively. Then, modular information of pathogens and hosts is added into bipartite network projection model and calculate association scores of pathogens and hosts. Finally, Leave-one-out cross-validation is used to estimate performance of the proposed method. Experimental results shown that the proposed method performs better on predicting pathogen-host association compared with other methods, and some potential pathogen-host associations with higher prediction score also have been confirmed by biological experiments from public literatures.