We propose here a grammatical evolution approach for the automatic discovery of Petri net models of biochemical systems that
are consistent with population level genetic models of disease susceptibility. We demonstrate the grammatical evolution approach
routinely identifies interesting and useful Petri net models in a human-competitive manner. This study opens the door for
hierarchical systems modeling of the relationship between genes, biochemistry, and measures of health.