A Novel Probability Model for LncRNA⁻Disease Association Prediction Based on the Naive Bayesian Classifier.

ABSTRACT: An increasing number of studies have indicated that long-non-coding RNAs (lncRNAs) play crucial roles in biological processes, complex disease diagnoses, prognoses, and treatments. However, experimentally validated associations between lncRNAs and diseases are still very limited. Recently, computational models have been developed to discover potential associations between lncRNAs and diseases by integrating multiple heterogeneous biological data; this has become a hot topic in biological research. In this article, we constructed a global tripartite network by integrating a variety of biological information including miRNA⁻disease, miRNA⁻lncRNA, and lncRNA⁻disease associations and interactions. Then, we constructed a global quadruple network by appending gene⁻lncRNA interaction, gene⁻diseas

SUBMITTER: Yu J 

PROVIDER: S-EPMC6071012 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature