A&A for modelling and engineering simulations in Systems Biology

Systems Biology (SB) promotes a system-level understanding of biological systems, and requires modelling and simulation tools for analysing biological systems dynamics. The articulation of Multiagent Systems (MASs) in terms of multiple, distributed and autonomous computational entities makes MAS a seemingly fit paradigm in SB. In this paper we adopt the Agents and Artefacts (A&A) metamodel where the notions of agent, artefact and workspace are taken as the basic bricks for MASs as the ontological foundation for our Multiagent-based Simulation (MABS) framework, and discuss how this impacts on SB. After recasting the A&A abstractions within the domain and design models, we specialise A&A within the SB context, and show an operational model based on the TuCSoN agent coordination infrastructure, upon which our simulation framework is implemented. As a case study, we model the well-studied metabolic pathway of glycolysis, and present some results of the simulation.