PWCDA: Path Weighted Method for Predicting circRNA-Disease Associations.

ABSTRACT: CircRNAs have particular biological structure and have proven to play important roles in diseases. It is time-consuming and costly to identify circRNA-disease associations by biological experiments. Therefore, it is appealing to develop computational methods for predicting circRNA-disease associations. In this study, we propose a new computational path weighted method for predicting circRNA-disease associations. Firstly, we calculate the functional similarity scores of diseases based on disease-related gene annotations and the semantic similarity scores of circRNAs based on circRNA-related gene ontology, respectively. To address missing similarity scores of diseases and circRNAs, we calculate the Gaussian Interaction Profile (GIP) kernel similarity scores for diseases and circRNAs, respect

SUBMITTER: Lei X 

PROVIDER: S-EPMC6274797 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature