The rapidly increasing number of revealed biological pathways calls for the development and use of simulation methods and tools that would facilitate their analysis and virtual experimentation. In this work we explore, examine, and compare two simulation methods, the Stochastic Pi-Calculus and Hybrid Functional Petri Nets, as they apply to metabolic pathways. The primary vehicle for our study is the Reduced Folates Metabolism, the pathway of nucleic acids precursors synthesis which is essential in cellular proliferation and therefore plays an important role in cancer research and chemotherapy. By employing appropriate and improved ways of modeling metabolic reactions, we introduce a novel real-world simulation model that allows several virtual experiments that involve different cancer chemotherapy drugs. Moreover, we investigate the steady state properties of special metabolic pathways in the two simulation methods.
Joint work with Yehuda Assaraf, Ilan Ifergan, and Wisam Kadry.