Establishing a massively parallel computational model of the adaptive immune response

IF 3.7 3区 计算机科学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Computational Science Pub Date : 2025-02-28 DOI:10.1016/j.jocs.2025.102555
Aristotle Martin, Max Nezdyur, Cyrus Tanade, Amanda Randles
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Abstract

Parallel agent-based models of the adaptive immune response can efficiently recapitulate emerging spatiotemporal properties of T-cell motility during clonal selection across multiple length and time scales. Here, we present a distributed, three-dimensional (3D) computational model of T-cell priming, and associated parallel data structures and algorithms that enable fully deterministic cell simulations at scale. We demonstrate performant usage of modern clusters with over 350x speedup, and explore trade-offs between simulation accuracy, code complexity, and communication overhead. This study highlights the potential for parallel 3D models to explore immunological research questions and guides implementation and performance considerations for this class of biology-inspired agent-based models.
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建立适应性免疫反应的大规模并行计算模型
基于并行agent的适应性免疫反应模型可以有效地概括在多个长度和时间尺度上克隆选择过程中t细胞运动的时空特性。在这里,我们提出了一个分布式的,三维(3D) t细胞启动的计算模型,以及相关的并行数据结构和算法,可以在规模上实现完全确定性的细胞模拟。我们展示了超过350倍加速的现代集群的性能使用情况,并探索了仿真精度、代码复杂性和通信开销之间的权衡。这项研究强调了并行3D模型探索免疫学研究问题的潜力,并指导了这类生物学启发的基于主体的模型的实现和性能考虑。
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来源期刊
Journal of Computational Science
Journal of Computational Science COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
5.50
自引率
3.00%
发文量
227
审稿时长
41 days
期刊介绍: Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It has reached a level of predictive capability that now firmly complements the traditional pillars of experimentation and theory. The recent advances in experimental techniques such as detectors, on-line sensor networks and high-resolution imaging techniques, have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data driven modeling and simulation. This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods. Computational science typically unifies three distinct elements: • Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous); • Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems; • Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).
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