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. 2018 Jan 29;8:1820. doi: 10.1038/s41598-018-20157-y

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© The Author(s) 2018

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Overview of the oriT structure-based prediction procedure. Based on an input oriT sequence, the computational procedure predicts (i) the MOB group of the particular oriT and plasmid as well as (ii) the range of potential transfer hosts and Inc/Rep types (see Discussion). Two types of predictive classification models are available to the user, based the training sets of either 64 or 200 elements.