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. 2020 Feb 18;21:59. doi: 10.1186/s12859-020-3390-4

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© The Author(s) 2020

Open Access This 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. 4 — Weights of the variables (genes) selected by sparse logistic regression via EN and twiner regularization, considering the ‘T-core/periphery vs. N-periphery’ case study (Model III); the variables are colored differently whether they are selected exclusively by EN (blue) or twiner (red), or selected in common by the two methods (gray)