SPCMLMI: A structural perturbation-based matrix completion method to predict lncRNA–miRNA interactions - Wang, Mei-Neng; Lei, Li-Lan; He, Wei; Ding, De-Wu (Frontiers in Genetics, 2022)
Accumulating evidences indicated that the interaction of lncRNA and miRNA is crucial for gene regulation, which can regulate gene transcription, further affecting the occurrence and development of many complex diseases. Accurate identification of interactions between lncRNAs and miRNAs is helpful for the diagnosis and therapeutic of complex diseases. However, the number of known interactions of lncRNA with miRNA is still very limited, and identifying their interactions by biological experiments is time-consuming and expensive, there is an urgent need to develop more accurate and efficient computational methods to infer lnRNA-miRNA interactions. In this work, we developed a matrix completion approach based on the structural perturbation to infer lncRNA-miRNA interactions (SPCMLMI). Specifically, we first calculated the similarities of lncRNA and miRNA, including lncRNA expression profile similarity, miRNA expression profile similarity, lncRNA sequence similarity and miRNA sequence similarity. Second, a bilayer network was constructed by integrating the known interaction network, lncRNA similarity network and miRNA similarity network. Finally, a structural perturbation-based matrix completion method was used to predict potential interactions of lncRNA with miRNA. To evaluate the prediction performance of SPCMLMI, five-fold cross validation as well as a series of comparison experiments were implemented. SPCMLMI achieved AUCs of 0.8984 and 0.9891 on two different datasets, which is superior to other compared methods. Case studies for lncRNA XIST and miRNA has-mir-195-5p further confirmed the effectiveness of our method in inferring lncRNA-miRNA interactions. Furthermore, we found that the structural consistency of the bilayer network was higher than that of other related networks. The results suggest that SPCMLMI can be used as a useful tool to predict interactions between lncRNAs and miRNAs.