Agent‐Based Modeling in Molecular Systems Biology. (8th June 2018)

• Record Type: Journal Article
• Authors: Soheilypour, Mohammad; Mofrad, Mohammad R. K.
• Is Part Of: BioEssays. Volume 40:Number 7(2018:Jul.)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-06-08
• Subjects: agent‐based modeling -- complex systems -- computational biology -- computational simulations -- molecular systems biology; Molecular biology -- Periodicals; Cytology -- Periodicals; Developmental biology -- Periodicals; 572.8
• DOI: 10.1002/bies.201800020
• Languages: English
• ISSNs: 0265-9247

Abstract

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. Abstract : Agent‐based Modeling (ABM) is a bottom‐up computational technique to efficiently simulate the evolution of stochastic and heterogeneous molecular systems. Molecules are represented as agents with governing rules defining how each individual agent moves and interacts with other agents, leading to reproduction of a complex phenomenon.