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. 2016 Sep 17;11:47. doi: 10.1186/s13062-016-0148-z

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© The Author(s). 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 — Receiver operating curves (ROCs) and area under curve values (AUCs) to quantify predictive power of our models. ROCs and AUCs show that our computational models can predict pluripotency genes in human (a-c) and mouse (b-d) stem-cells better than random expectations