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Int. J. Mol. Sci. 2015, 16(1), 1466-1481;

Prediction of Mature MicroRNA and Piwi-Interacting RNA without a Genome Reference or Precursors

Department of Information and Computer Sciences, University of Hawaii at Mānoa, 1680 East-West Road, Honolulu, HI 96822, USA
Authors to whom correspondence should be addressed.
Academic Editor: Martin Pichler
Received: 31 October 2014 / Accepted: 5 January 2015 / Published: 8 January 2015
(This article belongs to the Collection Regulation by Non-Coding RNAs)
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The discovery of novel microRNA (miRNA) and piwi-interacting RNA (piRNA) is an important task for the understanding of many biological processes. Most of the available miRNA and piRNA identification methods are dependent on the availability of the organism’s genome sequence and the quality of its annotation. Therefore, an efficient prediction method based solely on the short RNA reads and requiring no genomic information is highly desirable. In this study, we propose an approach that relies primarily on the nucleotide composition of the read and does not require reference genomes of related species for prediction. Using an empirical Bayesian kernel method and the error correcting output codes framework, compact models suitable for large-scale analyses are built on databases of known mature miRNAs and piRNAs. We found that the usage of an L1-based Gaussian kernel can double the true positive rate compared to the standard L2-based Gaussian kernel. Our approach can increase the true positive rate by at most 60% compared to the existing piRNA predictor based on the analysis of a hold-out test set. Using experimental data, we also show that our approach can detect about an order of magnitude or more known miRNAs than the mature miRNA predictor, miRPlex. View Full-Text
Keywords: microRNA; piwi-interacting RNA; non-coding RNAs; kernel machine; classification microRNA; piwi-interacting RNA; non-coding RNAs; kernel machine; classification

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Menor, M.S.; Baek, K.; Poisson, G. Prediction of Mature MicroRNA and Piwi-Interacting RNA without a Genome Reference or Precursors. Int. J. Mol. Sci. 2015, 16, 1466-1481.

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