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Open Access

Prediction of miRNA-circRNA Associations Based on k-NN Multi-Label with Random Walk Restart on a Heterogeneous Network

College of Computer Science, Shaanxi Normal University, Xi’an 710119, China.
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Abstract

Circular RNAs (circRNAs) play important roles in various biological processes, as essential non-coding RNAs that have effects on transcriptional and posttranscriptional gene expression regulation. Recently, many studies have shown that circRNAs can be regarded as micro RNA (miRNA) sponges, which are known to be associated with certain diseases. Therefore efficient computation methods are needed to explore miRNA-circRNA interactions, but only very few computational methods for predicting the associations between miRNAs and circRNAs exist. In this study, we adopt an improved random walk computational method, named KRWRMC, to express complicated associations between miRNAs and circRNAs. Our major contributions can be summed up in two points. First, in the conventional Random Walk Restart Heterogeneous (RWRH) algorithm, the computational method simply converts the circRNA/miRNA similarity network into the transition probability matrix; in contrast, we take the influence of the neighbor of the node in the network into account, which can suggest or stress some potential associations. Second, our proposed KRWRMC is the first computational model to calculate large numbers of miRNA-circRNA associations, which can be regarded as biomarkers to diagnose certain diseases and can thus help us to better understand complicated diseases. The reliability of KRWRMC has been verified by Leave One Out Cross Validation (LOOCV) and 10-fold cross validation, the results of which indicate that this method achieves excellent performance in predicting potential miRNA-circRNA associations.

Keywords

miRNA-circRNA associationsheterogeneous networkmulti-labelrandom walk restart

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Big Data Mining and Analytics
Volume 2 Issue 4,
December 2019
Pages 261-272
DOI: 10.26599/BDMA.2019.9020010
Cite this article:
Fang Z, Lei X. Prediction of miRNA-circRNA Associations Based on k-NN Multi-Label with Random Walk Restart on a Heterogeneous Network. Big Data Mining and Analytics, 2019, 2(4): 261-272. https://doi.org/10.26599/BDMA.2019.9020010

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Received: 25 November 2018
Revised: 16 April 2019
Accepted: 17 April 2019
Published: 05 August 2019
© The author(s) 2019

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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