A novel approach for predicting microbe-disease associations by bi-random walk on the heterogeneous network.

ABSTRACT: Since the microbiome has a significant impact on human health and disease, microbe-disease associations can be utilized as a valuable resource for understanding disease pathogenesis and promoting disease diagnosis and prognosis. Accordingly, it is necessary for researchers to achieve a comprehensive and deep understanding of the associations between microbes and diseases. Nevertheless, to date, little work has been achieved in implementing novel human microbe-disease association prediction models. In this paper, we develop a novel computational model to predict potential microbe-disease associations by bi-random walk on the heterogeneous network (BiRWHMDA). The heterogeneous network was constructed by connecting the microbe similarity network and the disease similarity network via known mi

SUBMITTER: Zou S 

PROVIDER: S-EPMC5589230 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature