The largest elementary effects on three key output variables at and .

<p>The effects on mean arterial pressure (MAP), cardiac output (QAO) and rate of urine production (VUD) are plotted as . Elementary effects were sorted by the magnitude of their largest effect on the three output variables. <b>A:</b> The elementary effects at (excluding HYL). <b>B:</b> The elementary effects at .</p

Parameters for building the virtual population.

<p>Parameters for building the virtual population.</p

Comparison of correlations between parameters and variables in the normotensive and hypertensive virtual sub-populations.

<p>For a given variable, the correlations with each parameter are plotted against the x-axis for the normotensive population, and against the y-axis for the hypertensive population (only correlations are shown). <b>A:</b> Mean arterial pressure (MAP). <b>B:</b> Cardiac output (QAO). <b>C:</b> Blood volume (VB). <b>D:</b> Rate of urine production (VUD).</p

The coefficients of each classifier (GLM) presented in Figure 8a.

<p>The coefficients of each classifier (GLM) presented in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002571#pcbi-1002571-g008" target="_blank">Figure 8a</a>.</p

Significant correlations between model parameters and the elementary effects of HYL at .

<p>Correlations () are shown for the elementary effect of HYL on mean arterial pressure (MAP), cardiac output (QAO) and rate of urine production (VUD).</p

The most significant elementary effects on three key output variables at each time .

<p><b>A:</b> The effects on mean arterial pressure (MAP), cardiac output (QAO) and rate of urine production (VUD) are plotted (at after the perturbations) as . <b>B:</b> The most significant elementary effects when HYL is ignored. The complete tables of elementary effects are included in the supplementary material.</p

Probability densities of model variables in the normotensive and hypertensive virtual sub-populations.

<p>Probability densities are shown for AAR (the afferent arteriolar resistance), POR (the reference value of capillary pressure in non-muscle tissue) and CPR (the critical plasma protein concentration for protein destruction).</p

Evaluation of linear classifiers for identifying hypertensive virtual individuals.

<p>Each classifier (binomial GLM) was fitted to a random sample of the virtual population and then evaluated on the remaining . <b>A:</b> ROC curves for several classifiers; the optimal (30-parameter) classifier has an area under curve (AUC) of , demonstrating high predictive power. The 6-parameter “Renal+Liver” classifier performs nearly as well (AUC = 0.948). <b>B:</b> The parameter sensitivity of the optimal classifier. The y-axis measures the variation in the prediction over the range of values for each parameter.</p

Significant correlations between model parameters and three key output variables.

<p>Correlations are shown for mean arterial pressure (MAP), cardiac output (QAO) and rate of urine production (VUD), where and .</p

The effects of aldosterone loading on the human body.

<p>This simulation reproduced the conditions shown in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002571#pcbi-1002571-g005" target="_blank">Figure 5</a> of Uttamsingh et al. <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002571#pcbi.1002571-Uttamsingh1" target="_blank">[74]</a>, which inclues experimental data from Davis and Howell <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002571#pcbi.1002571-Davis1" target="_blank">[94]</a> and Relman and Schwartz <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002571#pcbi.1002571-Relman1" target="_blank">[76]</a>. <b>A:</b> Extra-cellular fluid volume. <b>B:</b> Mean arterial pressure. <b>C:</b> Serum aldosterone (normalized). <b>D:</b> Sodium excretion rate.</p