In Silico Modeling in Infectious Disease.
In Silico Modeling in Infectious Disease.
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DOI：
10.1016/j.ddmod.2007.09.001
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发表时间：
2007-10-01
期刊：
影响因子：
--
通讯作者：
Clermont, Gilles
中科院分区：
文献类型：
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作者：
Daun, Silvia;Clermont, Gilles
传染病见证了数学建模的出现，这是一种合成日益复杂的数据的工具，现在可供临床医生和基础科学家使用。本综述的目的是介绍常用来模拟传染病的数学工具。我们将说明如何使用基于方程、基于代理或统计建模方法来处理与急性炎症、细菌动力学、病毒动力学和信号通路有关的各种示例，重点关注宿主-病原体相互作用而不是群体模型。我们将讨论这些方法的优点和缺点，并为这个快速发展的领域提供未来的前景。 Trevor Trust – 阿斯利康研发中心 Boston, 35 Gatehouse Drive, Waltham, MA 02451, USA
Infectious disease has witnessed the emergence of mathematical modeling a tool of synthesizing data of growing complexity now available to clinicians and basic scientists alike. The purpose of this review is to introduce mathematical tools commonly used to model infectious disease. We will illustrate the use of equation-based, agent-based or statistical modeling approaches to a variety of examples pertaining to acute inflammation, bacterial dynamics, viral dynamics, and signaling pathways, focusing of host-pathogen interactions rather than population models. We will discuss the strengths and weaknesses of these approaches and offer future perspectives for this rapidly evolving field. Trevor Trust – AstraZeneca R&D Boston, 35 Gatehouse Drive, Waltham, MA 02451, USA