ncRNAInter: a novel strategy based on graph neural network to discover interactions between lncRNA and miRNA

Abstract

In recent years, many studies have illustrated the significant role that non-coding RNA (ncRNA) plays in biological activities, in which lncRNA, miRNA and especially their interactions have been proved to affect many biological processes. Some in silico methods have been proposed and applied to identify novel lncRNA–miRNA interactions (LMIs), but there are still imperfections in their RNA representation and information extraction approaches, which imply there is still room for further improving their performances. Meanwhile, only a few of them are accessible at present, which limits their practical applications. The construction of a new tool for LMI prediction is thus imperative for the better understanding of their relevant biological mechanisms. This study proposed a novel method, ncRNAInter, for LMI prediction. A comprehensive strategy for RNA representation and an optimized deep learning algorithm of graph neural network were utilized in this study. ncRNAInter was robust and showed better performance of 26.7% higher Matthews correlation coefficient than existing reputable methods for human LMI prediction. In addition, ncRNAInter proved its universal applicability in dealing with LMIs from various species and successfully identified novel LMIs associated with various diseases, which further verified its effectiveness and usability. All source code and datasets are freely available at https://github.com/idrblab/ncRNAInter.

MOINER: A Novel Multiomics Early Integration Framework for Biomedical Classification and Biomarker Discovery

“…Other genes identified by MOINER, such as GPER1 and CDK2AP1 , had also been proved to be associated with AD. Moreover, highly ranking miRNAs identified by MOINER, such as has-mir-129-5p , has-mir-132 , , has-mir-376a , and has-mir-127–3p et al, had also been reported to be associated with AD . For instance, there is an association between the expression of miR-129-5p in serum and the levels of cognitive function markers in AD patients .…”

“…Moreover, highly ranking miRNAs identified by MOINER, such as has-mir-129-5p, 62 has-mir-132, 63,64 has-mir-376a, 65 and has-mir-127−3p 66 et al, had also been reported to be associated with AD. 67 For instance, there is an association between the expression of miR-129-5p in serum and the levels of cognitive function markers in AD patients. 62 The validation of important features identified by MOINER against existing experimental literature under-scores the promising applications of MOINER in the discovery of potential biomarkers for disease diagnosis in clinical practice.…”

Deep Learning Approaches for lncRNA-Mediated Mechanisms: A Comprehensive Review of Recent Developments

“…Despite not mentioning specific disadvantages, the method managed to integrate an lncRNA-miRNA similarity network to achieve high AUC scores. The study by [ 76 ] applied a graph neural network-based RNA representation technique, termed ncRNAInter, and demonstrated robust performance and broad applicability across different species.…”

“…As we delve into the intricacies of lncRNA–miRNA associations, one can observe a clear trend toward leveraging advanced machine learning models for predicting these interactions, as evidenced by the studies summarized in Table 4 . A noteworthy focus has been on developing deep learning frameworks that offer both improved accuracy and applicability across various species [ 75 , 76 , 77 , 80 ].…”

Exploring miRNA–target gene pair detection in disease with coRmiT

“…However, only TargetScan and miRDB have been consistently updated over the last 8 years [ 10 ] and the precision of recently published predictive tools is still low when compared with high-throughput validation datasets [ 9 , 11 , 12 ]. In recent years, new tools based on deep learning have emerged, such as DMISO [ 13 ], TargetNet [ 14 ], miRBind [ 15 ] and ncRNAInter [ 16 ].…”