Department of Surgery, Immunology, Computational & Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania.
Department of Bioengineering, University of Pittsburgh, Pittsburgh, Pennsylvania.
Wiley Interdiscip Rev Syst Biol Med. 2019 Nov;11(6):e1460. doi: 10.1002/wsbm.1460. Epub 2019 Jul 1.
Agent-based modeling is a rule-based, discrete-event, and spatially explicit computational modeling method that employs computational objects that instantiate the rules and interactions among the individual components ("agents") of system. Agent-based modeling is well suited to translating into a computational model the knowledge generated from basic science research, particularly with respect to translating across scales the mechanisms of cellular behavior into aggregated cell population dynamics manifesting at the tissue and organ level. This capacity has made agent-based modeling an integral method in translational systems biology (TSB), an approach that uses multiscale dynamic computational modeling to explicitly represent disease processes in a clinically relevant fashion. The initial work in the early 2000s using agent-based models (ABMs) in TSB focused on examining acute inflammation and its intersection with wound healing; the decade since has seen vast growth in both the application of agent-based modeling to a wide array of disease processes as well as methodological advancements in the use and analysis of ABM. This report presents an update on an earlier review of ABMs in TSB and presents examples of exciting progress in the modeling of various organs and diseases that involve inflammation. This review also describes developments that integrate the use of ABMs with cutting-edge technologies such as high-performance computing, machine learning, and artificial intelligence, with a view toward the future integration of these methodologies. This article is categorized under: Translational, Genomic, and Systems Medicine > Translational Medicine Models of Systems Properties and Processes > Mechanistic Models Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models Models of Systems Properties and Processes > Organismal Models.
基于代理的建模是一种基于规则、离散事件和空间显式的计算建模方法，它使用计算对象来实例化系统中各个组件（“代理”）之间的规则和交互。基于代理的建模非常适合将基础科学研究中生成的知识转化为计算模型，特别是在将细胞行为的机制跨越多个尺度转化为表现为组织和器官水平的聚集细胞群体动态方面。这种能力使基于代理的建模成为转化系统生物学（TSB）的一种整体方法，该方法使用多尺度动态计算建模以临床相关的方式明确表示疾病过程。21 世纪初在 TSB 中使用基于代理的模型（ABM）的初步工作集中在检查急性炎症及其与伤口愈合的交叉；此后的十年中，基于代理的建模在广泛的疾病过程中的应用以及在使用和分析 ABM 方面的方法学进展都取得了巨大的增长。本报告更新了早期关于 TSB 中 ABM 的综述，并介绍了涉及炎症的各种器官和疾病建模方面令人兴奋的进展示例。这篇综述还描述了将 ABM 与高性能计算、机器学习和人工智能等前沿技术结合使用的发展情况，以期未来整合这些方法。本文属于以下类别：转化、基因组和系统医学 > 转化医学系统特性和过程模型 > 机制模型系统特性和过程模型 > 器官、组织和生理模型系统特性和过程模型 > 生物体模型。
