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. 2014 Dec 24;14:14. doi: 10.1186/s12899-014-0014-0

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© Ippolito et al.; licensee BioMed Central. 2014

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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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Random forest analysis accurately discriminates heat exposure from unheated controls at 24 hours. The top 30 metabolites were identified in OOB selection to have 94% predictive power by random forest analysis at T_c,Max. The inset represents predictive power of the 30 biochemicals identified. Colored circles indicate biochemicals that were also significantly up (red) or down (green) regulated, p < 0.05, 2-way ANOVA with contrasts. One biochemical was not significantly altered by ANOVA analysis (yellow). Biochemicals marked by an asterisk indicate likely identifications based on MS/MS fragmentation and other chemical properties.