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. 2019 May 14;9:7344. doi: 10.1038/s41598-019-43708-3

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© The Author(s) 2019

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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The representation of an individual multi-task feed-forward DNN model of DEEPred (i.e., model N). Here, each task at the output layer (i.e., red squares) corresponds to a different GO term. In the example above, a query input vector is fed to the trained model N and a score greater than the pre-defined threshold is produced for GON,3, which is marked as a prediction.