LncRNA-Disease Association Prediction Using Two-Side Sparse Self-Representation.

ABSTRACT: Evidences increasingly indicate the involvement of long non-coding RNAs (lncRNAs) in various biological processes. As the mutations and abnormalities of lncRNAs are closely related to the progression of complex diseases, the identification of lncRNA-disease associations has become an important step toward the understanding and treatment of diseases. Since only a limited number of lncRNA-disease associations have been validated, an increasing number of computational approaches have been developed for predicting potential lncRNA-disease associations. However, how to predict potential associations precisely through computational approaches remains challenging. In this study, we propose a novel two-side sparse self-representation (TSSR) algorithm for lncRNA-disease association prediction. By l

SUBMITTER: Ou-Yang L 

PROVIDER: S-EPMC6546878 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature