KGDCMI: A New Approach for Predicting circRNA-miRNA Interactions From Multi-Source Information Extraction and Deep Learning.

ABSTRACT: Emerging evidence has revealed that circular RNA (circRNA) is widely distributed in mammalian cells and functions as microRNA (miRNA) sponges involved in transcriptional and posttranscriptional regulation of gene expression. Recognizing the circRNA-miRNA interaction provides a new perspective for the detection and treatment of human complex diseases. Compared with the traditional biological experimental methods used to predict the association of molecules, which are limited to the small-scale and are time-consuming and laborious, computing models can provide a basis for biological experiments at low cost. Considering that the proposed calculation model is limited, it is necessary to develop an effective computational method to predict the circRNA-miRNA interaction. This study thus proposed

SUBMITTER: Wang XF 

PROVIDER: S-EPMC9426772 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature