LDAPred: A Method Based on Information Flow Propagation and a Convolutional Neural Network for the Prediction of Disease-Associated lncRNAs.

ABSTRACT: Long non-coding RNAs (lncRNAs) play a crucial role in the pathogenesis and development of complex diseases. Predicting potential lncRNA-disease associations can improve our understanding of the molecular mechanisms of human diseases and help identify biomarkers for disease diagnosis, treatment, and prevention. Previous research methods have mostly integrated the similarity and association information of lncRNAs and diseases, without considering the topological structure information among these nodes, which is important for predicting lncRNA-disease associations. We propose a method based on information flow propagation and convolutional neural networks, called LDAPred, to predict disease-related lncRNAs. LDAPred not only integrates the similarities, associations, and interactions among lnc

SUBMITTER: Xuan P 

PROVIDER: S-EPMC6771133 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature