Multiscale Computing in Systems Medicine: a Brief Reflection

Huiru Zheng, Jyotsna Talreja Wassan, M. Moisescu, L. Stoicu-Tivadar, J. Miranda, Mihaela Crișan-Vida, I. Sacala, A. Badnjević, I. Chorbev, B. Jakimovski
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引用次数: 2

Abstract

Today’s modelling approaches in Systems Medicine are increasingly multiscale, containing two or more submodels, where each operates on different temporal and/or spatial scales. In addition, as these models become increasingly sophisticated, they tend to be run as multiscale computing applications using computational infrastructures such as clusters, supercomputers, grids or clouds. Constructing, validating and deploying such applications is far from trivial, and communities in different scientific disciplines have chosen very diverse approaches to address these challenges. Within this paper we reflect on the use of Multiscale Computing within the context of Systems Medicine. Multiscale Computing is widely applied within this area, and instead of summarizing the field as a whole we will highlight a set of challenges that we believe are of key relevance to the Systems Medicine community.
系统医学中的多尺度计算:一个简短的反思
当今系统医学的建模方法越来越多地是多尺度的,包含两个或更多的子模型,其中每个子模型在不同的时间和/或空间尺度上运行。此外,随着这些模型变得越来越复杂,它们倾向于作为使用计算基础设施(如集群、超级计算机、网格或云)的多尺度计算应用程序运行。构建、验证和部署这样的应用程序远非易事,不同科学学科的社区选择了非常不同的方法来解决这些挑战。在本文中,我们反思了在系统医学的背景下使用多尺度计算。多尺度计算在这一领域得到了广泛的应用,而不是将该领域作为一个整体进行总结,我们将重点介绍我们认为与系统医学社区关键相关的一系列挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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