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miRTRS: A Recommendation Algorithm for Predicting miRNA Targets | IEEE Journals & Magazine | IEEE Xplore

miRTRS: A Recommendation Algorithm for Predicting miRNA Targets


Abstract:

microRNAs (miRNAs) are small and important non-coding RNAs that regulate gene expression in transcriptional and post-transcriptional level by combining with their targets...Show More

Abstract:

microRNAs (miRNAs) are small and important non-coding RNAs that regulate gene expression in transcriptional and post-transcriptional level by combining with their targets (genes). Predicting miRNA targets is an important problem in biological research. It is expensive and time-consuming to identify miRNA targets by using biological experiments. Many computational methods have been proposed to predict miRNA targets. In this study, we develop a novel method, named miRTRS, for predicting miRNA targets based on a recommendation algorithm. miRTRS can predict targets for an isolated (new) miRNA with miRNA sequence similarity, as well as isolated (new) targets for a miRNA with gene sequence similarity. Furthermore, when compared to supervised machine learning methods, miRTRS does not need to select negative samples. We use 10-fold cross validation and independent datasets to evaluate the performance of our method. We compared miRTRS with two most recently published methods for miRNA target prediction. The experimental results have shown that our method miRTRS outperforms competing prediction methods in terms of AUC and other evaluation metrics.
Published in: IEEE/ACM Transactions on Computational Biology and Bioinformatics ( Volume: 17, Issue: 3, 01 May-June 2020)
Page(s): 1032 - 1041
Date of Publication: 01 October 2018

ISSN Information:

PubMed ID: 30281478

Funding Agency:


References

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