An Agent-based Modeling Approach for Stochastic Molecular Events of Biochemical Networks

Abstract

Modeling and simulation of intracellular biochemical networks is a critical method to study the biological system behaviors. The phenomena of self-organization play a crucial role in biological systems and Agent-based modeling (ABM) has been widely viewed as a computational framework to study the complex systems. Agent-based modeling approach has tremendous potential in advancing studying the phenomena of self-organization in biochemical networks, but is still under-utilized both in theory and practice. In this study we present a new bottom-up computational modeling and simulation paradigm -- Agent-Based Modeling (ABM) with Reaction Agents (ABM-RA) which models the biochemical networks based on self-organization and is a mathematical formalization of a multi-agent system for the biochemical reaction networks. Experiment results show that ABM-RA is a generic approach. It is thus a fundamentally better fit to a real biological system than the top-down approach which relies heavily on human abstractions.