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Automatic 3D cluster modelling of COVID-19 through voxel-based redistribution
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 complexit...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9588143/ https://www.ncbi.nlm.nih.gov/pubmed/36313254 http://dx.doi.org/10.1016/j.powtec.2021.05.083 |
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author | Wang, Mingzhi Liu, Yushi Qi, Beimeng Wang, Wei |
author_facet | Wang, Mingzhi Liu, Yushi Qi, Beimeng Wang, Wei |
author_sort | Wang, Mingzhi |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9588143 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95881432022-10-24 Automatic 3D cluster modelling of COVID-19 through voxel-based redistribution Wang, Mingzhi Liu, Yushi Qi, Beimeng Wang, Wei Powder Technol Article 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. Elsevier B.V. 2021-09 2021-05-25 /pmc/articles/PMC9588143/ /pubmed/36313254 http://dx.doi.org/10.1016/j.powtec.2021.05.083 Text en © 2021 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Wang, Mingzhi Liu, Yushi Qi, Beimeng Wang, Wei Automatic 3D cluster modelling of COVID-19 through voxel-based redistribution |
title | Automatic 3D cluster modelling of COVID-19 through voxel-based redistribution |
title_full | Automatic 3D cluster modelling of COVID-19 through voxel-based redistribution |
title_fullStr | Automatic 3D cluster modelling of COVID-19 through voxel-based redistribution |
title_full_unstemmed | Automatic 3D cluster modelling of COVID-19 through voxel-based redistribution |
title_short | Automatic 3D cluster modelling of COVID-19 through voxel-based redistribution |
title_sort | automatic 3d cluster modelling of covid-19 through voxel-based redistribution |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9588143/ https://www.ncbi.nlm.nih.gov/pubmed/36313254 http://dx.doi.org/10.1016/j.powtec.2021.05.083 |
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