Grammatical Evolution for the Discovery of Petri Net Models of Complex Genetic Systems

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.