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. 2020 Oct 1;10:16191. doi: 10.1038/s41598-020-73105-0

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© The Author(s) 2020

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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

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TSNE dimensionality reduction of chemical embeddings with health associations. TSNE plots of Mol2Vec chemical embeddings for garlic (A–C) and cocoa (D–F). The colors of each data point encode the number of health implications associated with the compounds based on the CTD database. Dark gray represents chemicals with 0 health associations. We show chemicals catalogued by each studied database for FoodMine (A,D), USDA (B,E), and FooDB (C,F). Markers are filled if the database contains the chemical, and empty if it does not.