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Open AccessArticle

WebCircRNA: Classifying the Circular RNA Potential of Coding and Noncoding RNA

1
Center for Non-Coding RNA in Technology and Health, University of Copenhagen, 1870 Frederiksberg C, Denmark
2
Department of Veterinary and Animal Sciences, University of Copenhagen, 1870 Frederiksberg C, Denmark
3
Department of Disease Systems Biology, Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen, Denmark
4
BrainStem—Stem Cell Center of Excellence in Neurology, University of Copenhagen, 1870 Frederiksberg C, Denmark
*
Authors to whom correspondence should be addressed.
Genes 2018, 9(11), 536; https://doi.org/10.3390/genes9110536
Received: 7 September 2018 / Revised: 29 October 2018 / Accepted: 2 November 2018 / Published: 6 November 2018
(This article belongs to the Special Issue Computational Analysis of RNA Structure and Function)
Circular RNAs (circRNAs) are increasingly recognized to play crucial roles in post-transcriptional gene regulation including functioning as microRNA (miRNA) sponges or as wide-spread regulators, for example in stem cell differentiation. It is therefore highly relevant to identify if a transcript of interest can also function as a circRNA. Here, we present a user-friendly web server that predicts if coding and noncoding RNAs have circRNA isoforms and whether circRNAs are expressed in stem cells. The predictions are made by random forest models using sequence-derived features as input. The output scores are converted to fractiles, which are used to assess the circRNA and stem cell potential. The performances of the three models are reported as the area under the receiver operating characteristic (ROC) curve and are 0.82 for coding genes, 0.89 for long noncoding RNAs (lncRNAs) and 0.72 for stem cell expression. We present WebCircRNA for quick evaluation of human genes and transcripts for their circRNA potential, which can be essential in several contexts. View Full-Text
Keywords: circular RNA; random forest; noncoding RNA circular RNA; random forest; noncoding RNA
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Pan, X.; Xiong, K.; Anthon, C.; Hyttel, P.; Freude, K.K.; Jensen, L.J.; Gorodkin, J. WebCircRNA: Classifying the Circular RNA Potential of Coding and Noncoding RNA. Genes 2018, 9, 536.

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