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. 2018 Apr 26;8:6620. doi: 10.1038/s41598-018-24937-4

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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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Samples from different cancer types and their random partition into training and test sets. Each sample (represented using a vector of 1239 TFs expressions) is mapped onto a 2-dimensional space using multidimensional scaling. Samples of various cancer types of PanCan12 dataset are shown in different colors. Circles represent test samples (i.e., test conditions) and crosses represent training samples.