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. 2018 Nov 20;19(Suppl 14):411. doi: 10.1186/s12859-018-2379-8

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© The Author(s). 2018

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 — Supervised model of TMFUF. In the training phase, both A and F are used to calculate the symmetric projection matrix Θ. In the predicting model, the feature vectors and the projection matrix Θ are used to deduce potential DDIs for T₁ and T₂