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. 2016 Apr 23;11:8. doi: 10.1186/s13015-016-0070-z

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© Lorenz et al. 2016

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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Fig. 2 — Prediction performance for tRNAdb benchmark set. Treating chemically modified bases as unpaired increases both sensitivity and positive predictive value on the tRNAdb benchmark set. 95 % confidence intervals were estimated using bootstrapping with 1000 iterations