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. Author manuscript; available in PMC: 2010 Mar 16.
Published in final edited form as: Bioinformatics. 2007 Oct 5;23(21):2910–2917. doi: 10.1093/bioinformatics/btm483

Fig. 1.

Fig. 1

An integrative model outperforms every one of its component obesity-related experiments. A. Receiver-operating characteristic curves are plotted for each of 49 obesity-related experiments and by experimental modality. An integrative model, considering genes by the number of obesity-related experiments in which they were positive, is shown in black. Each point on this curve indicates a different threshold number of positive experiments. Model error bars were constructed using 100 trials of 10-fold cross-validation, and indicate ± 1 standard deviation. B. Violin-plot showing the distribution of areas under the ROC curves for 100 cross-validated trials of the integrative model and the 49 individual obesity-related experiments. Significance was assessed using the Wilcoxon rank sum test. White dot indicates median, box covers between the 25% and 75% quantiles, whiskers cover extreme data points within 1.5 times the interquartile range from the box, and gray indicates the distribution of points.

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