A Network Based Method for Analysis of lncRNA-Disease Associations and Prediction of lncRNAs Implicated in Diseases

• DOI: 10.1371/journal.pone.0087797
• Publication Date: 2014-01-31T17:59:02Z
• Authors: Xiaofei Yang; Lin Gao; Xingli Guo; Xinghua Shi; Hao Wu; Fei Song; Bingbo Wang
• Keywords: Gene regulatory network

Increasing evidence has indicated that long non-coding RNAs (lncRNAs) are implicated in and associated with many complex human diseases. Despite of the accumulation lncRNA-disease associations, only a few studies had studied roles these associations pathogenesis. In this paper, we investigated from network view to understand contribution lncRNAs Specifically, both properties diseases which were implicated, Regarding fact protein coding genes involved diseases, constructed coding-non-coding gene-disease bipartite based on known between disease-causing genes. We then applied propagation algorithm uncover hidden network. The was evaluated by leave-one-out cross validation 103 at least two be involved, achieved an AUC 0.7881. Our successfully predicted 768 potential 66 193 Furthermore, our results for Alzheimer's disease, pancreatic cancer, gastric cancer verified other independent studies.