BJLD-CMI: a predictive circRNA-miRNA interactions model combining multi-angle feature information - Zhao, Yi-Xin; Yu, Chang-Qing; Li, Li-Ping; Wang, Deng-Wu; Song, Hui-Fan; Wei, Yu (Frontiers in Genetics, 2024)
Increasing research findings suggest that circular RNA (circRNA) exerts a crucial function in the pathogenesis of complex human diseases by binding to miRNA. Identifying their potential interactions is of paramount importance for the diagnosis and treatment of diseases. However, long cycles, small scales, and time-consuming processes characterize previous biological wet experiments. Consequently, the use of an efficient computational model to forecast the interactions between circRNA and miRNA is gradually becoming mainstream. In this study, we present a new prediction model named BJLD-CMI. The model predicts potential circRNA-miRNA interactions by integrating multi-angle feature information, including circRNA sequence data, miRNA sequence data, and known circRNA-miRNA interactions. BJLD-CMI attained 94.95% and 90.69% of the area under the ROC curve on the CMI-9589 and CMI 9905 datasets. When compared with existing models, the results indicate that BJLD-CMI exhibits the best overall competence. During the case study experiment, we conducted a PubMed literature search to confirm that out of the top 10 predicted CMIs, seven pairs did indeed exist.