Agent‐Based Modeling in Molecular Systems Biology

Abstract

Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems at different spatiotemporal scales, there is still a need for methods that bridge the gap between spatially-detailed and computationally-efficient approaches. In this review, we summarize the capabilities of agent-based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease.

Trends in mathematical modeling of host–pathogen interactions

“…The bottom-up approach, including ABM or cellular automata (CA) such as the famous 'Game of life' [42], works at a microscopic level [13,14,118]. Both ABM and CA are suitable methods to simulate the behavior of a system in a spatio-temporal manner.…”

“…Both ABM and CA are suitable methods to simulate the behavior of a system in a spatio-temporal manner. However, CA are gridbased and do not allow a free movement in space as the (usually) lattice-free ABM does [14,21,96,118]. Thus, ABM can be considered as an extension or generalization of CA [26,96].…”

“…Thus, ABM can be considered as an extension or generalization of CA [26,96]. In the unconventional ABM approach, individual independent agents are defined (such as fungal, bacterial, or human cells) with interaction rules [7,13,21,44,96,118]. Individual interactions (usually between nearest neighbors) are simulated rather than global conditions [7,21,30,114].…”

Application of agent-based modelling to assess single-molecule transport across the cell envelope of E. coli

“…As an alternative, the construction and simulation of in silico molecular models can help understand cell envelope processes and cellular behaviour [9]. Specifically, agent-based models (ABM) have shown great potential to simulate biological events [10][11][12][13][14]. Typically, these models represent the cell as a complex environment, where single molecules are described as individual agents that are influenced by their surroundings.…”

Mechanobiology of the Nuclear Pore Complex Machinery

“…[1]. Using a hybrid of computational modeling approaches, ranging from finite element [3] to coarse-grained Brownian dynamics [4] to molecular dynamics techniques [5] to new agent-based modeling methods [6][7][8], we study the structure and function of the nuclear pore complex and the dynamics of nucleocytoplasmic traffic. Understanding the mechanobiology of the nuclear pore complex and nucleocytoplasmic transport will broadly impact our understanding of viral diseases and may revolutionize therapeutic approaches (e.g.…”