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. 2012 Mar 13;40(11):e87. doi: 10.1093/nar/gks230

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© The Author(s) 2012. Published by Oxford University Press.

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Figure 6. — Procedure overview for EXPAR template classification using (A) a PWM approach, and (B) a Naïve Bayes classification method. In each case, 90% of the total data set consisting of Class I and II templates was used as training set to derive a model that was then applied to classify the templates in the remaining 10% used as test set. The process is repeated 10 times, each time using a different part of the total data set as test set.