John A Lees, Timothy W Russell, Liam P Shaw, Joel Hellewell
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引用次数: 0
Abstract
In this review, we assess the status of computational modelling of pathogens. We focus on three disparate but interlinked research areas that produce models with very different spatial and temporal scope. First, we examine antimicrobial resistance (AMR). Many mechanisms of AMR are not well understood. As a result, it is hard to measure the current incidence of AMR, predict the future incidence, and design strategies to preserve existing antibiotic effectiveness. Next, we look at how to choose the finite number of bacterial strains that can be included in a vaccine. To do this, we need to understand what happens to vaccine and non-vaccine strains after vaccination programmes. Finally, we look at within-host modelling of antibody dynamics. The SARS-CoV-2 pandemic produced huge amounts of antibody data, prompting improvements in this area of modelling. We finish by discussing the challenges that persist in understanding these complex biological systems.
在本综述中,我们将评估病原体计算建模的现状。我们重点关注三个不同但相互关联的研究领域,这些领域产生的模型在空间和时间范围上存在很大差异。首先,我们研究了抗菌剂耐药性(AMR)。人们对 AMR 的许多机制还不甚了解。因此,很难衡量当前的抗药性发生率、预测未来的发生率,以及制定战略来保持现有抗生素的有效性。接下来,我们将探讨如何选择可纳入疫苗的有限数量的细菌菌株。为此,我们需要了解疫苗接种计划后疫苗菌株和非疫苗菌株会发生什么变化。最后,我们将研究抗体动态的宿主内部模型。SARS-CoV-2 大流行产生了大量抗体数据,促使这一领域的建模工作有所改进。最后,我们讨论了在理解这些复杂生物系统方面依然存在的挑战。
期刊介绍:
Life Science Alliance is a global, open-access, editorially independent, and peer-reviewed journal launched by an alliance of EMBO Press, Rockefeller University Press, and Cold Spring Harbor Laboratory Press. Life Science Alliance is committed to rapid, fair, and transparent publication of valuable research from across all areas in the life sciences.