A novel target convergence set based random walk with restart for prediction of potential LncRNA-disease associations.

ABSTRACT:

Background

In recent years, lncRNAs (long-non-coding RNAs) have been proved to be closely related to the occurrence and development of many serious diseases that are seriously harmful to human health. However, most of the lncRNA-disease associations have not been found yet due to high costs and time complexity of traditional bio-experiments. Hence, it is quite urgent and necessary to establish efficient and reasonable computational models to predict potential associations between lncRNAs and diseases.

Results

In this manuscript, a novel prediction model called TCSRWRLD is proposed to predict potential lncRNA-disease associations based on improved random walk with restart. In TCSRWRLD, a heterogeneous lncRNA-disease network is constructed first by combining the integrated sim

SUBMITTER: Li J 

PROVIDER: S-EPMC6889579 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature