Using Network Distance Analysis to Predict lncRNA –miRNA Interactions

In this study, we developed a network distance analysis model for lncRNA–miRNA association prediction (NDALMA). Similarity networks for lncRNAs and miRNAs were calculated and integrated with Gaussian interaction profile (GIP) kernel similarity. Then, network distance analysis was applied to the integrated similari ty networks, and final scores were obtained after confidence calculation and score conversion. Our model obtained satisfactory results in fivefold cross validation, achieving an AUC of 0.8810 and an AUPR of 0.8315. Moreover, NDALMA showed superior prediction performance over several other network al gorithms, and we tested the suitability and flexibility of the model by comparing different types of similarity. In addition, case studies of the relationships between lncRNAs and miRNAs were conducted, which verified the reliability of our method in predicting lncRNA–miRNA associations. The datas ets and source code used in this study are available athttps://github.com/Liu-Lab-Lnu/NDALMA.Graphic Abstract

Source: Interdisciplinary Sciences, Computational Life Sciences - July 7, 2021 Category: Bioinformatics Source Type: research