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通过基于体素的重新分布对新型冠状病毒肺炎进行自动三维聚类建模

Automatic 3D cluster modelling of COVID-19 through voxel-based redistribution.

作者信息

Wang Mingzhi, Liu Yushi, Qi Beimeng, Wang Wei

机构信息

School of Civil Engineering, Harbin Institute of Technology, Harbin 150090, China.

Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education, Harbin Institute of Technology, Harbin 150090, China.

出版信息

Powder Technol. 2021 Sep;390:174-181. doi: 10.1016/j.powtec.2021.05.083. Epub 2021 May 25.

Abstract

Computational analysis of virus dynamics provides a non-contact environment for the study of the vital object. Cluster modelling is an essential step to investigate the properties of a group of viruses, and an automatic approach is required for massive 3D data processing. The morphological complexity of individual virus limits the application of smooth function algorithms with a regular-shaped assumption. This paper proposed a voxel-based redistribution approach to generate the virus cluster with COVID-19 input automatically. Representative elementary volume analysis was performed to address the statistical influence from the digital sample size. Coordination number analysis and surface density measurement were conducted with COVID-19 input and spherical input for comparison. The proposed approach is in natural compatibility with the lattice Boltzmann method for fluid dynamics analysis. A virtual permeation simulation was performed with the COVID-19 cluster and spherical cluster to demonstrate the necessity to include spike protein structure in the cluster modelling.

摘要

病毒动力学的计算分析为研究重要对象提供了一个非接触环境。聚类建模是研究一组病毒特性的关键步骤,而大规模三维数据处理需要一种自动方法。单个病毒的形态复杂性限制了基于规则形状假设的光滑函数算法的应用。本文提出了一种基于体素的重新分布方法,以自动生成输入新冠病毒的病毒簇。进行了代表性基本体积分析,以解决数字样本大小的统计影响。对输入新冠病毒和球形输入进行了配位数分析和表面密度测量以作比较。所提出的方法与用于流体动力学分析的格子玻尔兹曼方法自然兼容。对输入新冠病毒的簇和球形簇进行了虚拟渗透模拟,以证明在簇建模中纳入刺突蛋白结构的必要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cc02/9588143/00a516d8a12c/ga1_lrg.jpg

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