Orion: a spatial Multi Agent System framework for Computational Cellular Dynamics of metabolic pathways

Computational models that reproduce and predict the detailed behavior of cellular systems form the Holy Grail of systems biology [1]. Molecular Dynamics represents the most accurate and fundamental approach to cell simulation, taking into account the fundamental physical rules at the atomic level. Due to the incredible high number of atoms that must be considered, it cannot be practically used to simulate whole cell systems. A plethora of other mathematical and computational approaches are therefore applied -often experimentally- in systems biology, aiming at the modeling and simulation of cellular systems and processes (e.g. Ordinary Differential Equations, Partial Differential Equations, Petri Nets, UML, PI calculus, Multi Agent Systems, Dynamic Cellular Automata). Methods can be differentiated [2] according to the resolution levels adopted in space, scale and time representation, presence or absence of stochasticity, level of abstraction and to many other factors. The choice of the method implies critical consequences on the model's engineering cycle of life. Issues like accuracy, availability of formal methods to verify properties of the systems, modularity, questions that the model can answer, intuitiveness, scalability, practicability, usefulness for the biological community, existence of suitable experimental data, should all be accurately weighted when choosing a modeling and simulation framework.