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Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking
The SARS-CoV-2 genomic data continue to grow, providing valuable information for researchers and public health officials. Genomic analysis of these data sheds light on the transmission and evolution of the virus. To aid in SARS-CoV-2 genomic analysis, many web resources have been developed to store,...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10222785/ https://www.ncbi.nlm.nih.gov/pubmed/37243244 http://dx.doi.org/10.3390/v15051158 |
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author | Cheng, Yexiao Ji, Chengyang Zhou, Hang-Yu Zheng, Heng Wu, Aiping |
author_facet | Cheng, Yexiao Ji, Chengyang Zhou, Hang-Yu Zheng, Heng Wu, Aiping |
author_sort | Cheng, Yexiao |
collection | PubMed |
description | The SARS-CoV-2 genomic data continue to grow, providing valuable information for researchers and public health officials. Genomic analysis of these data sheds light on the transmission and evolution of the virus. To aid in SARS-CoV-2 genomic analysis, many web resources have been developed to store, collate, analyze, and visualize the genomic data. This review summarizes web resources used for the SARS-CoV-2 genomic epidemiology, covering data management and sharing, genomic annotation, analysis, and variant tracking. The challenges and further expectations for these web resources are also discussed. Finally, we highlight the importance and need for continued development and improvement of related web resources to effectively track the spread and understand the evolution of the virus. |
format | Online Article Text |
id | pubmed-10222785 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102227852023-05-28 Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking Cheng, Yexiao Ji, Chengyang Zhou, Hang-Yu Zheng, Heng Wu, Aiping Viruses Review The SARS-CoV-2 genomic data continue to grow, providing valuable information for researchers and public health officials. Genomic analysis of these data sheds light on the transmission and evolution of the virus. To aid in SARS-CoV-2 genomic analysis, many web resources have been developed to store, collate, analyze, and visualize the genomic data. This review summarizes web resources used for the SARS-CoV-2 genomic epidemiology, covering data management and sharing, genomic annotation, analysis, and variant tracking. The challenges and further expectations for these web resources are also discussed. Finally, we highlight the importance and need for continued development and improvement of related web resources to effectively track the spread and understand the evolution of the virus. MDPI 2023-05-12 /pmc/articles/PMC10222785/ /pubmed/37243244 http://dx.doi.org/10.3390/v15051158 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Cheng, Yexiao Ji, Chengyang Zhou, Hang-Yu Zheng, Heng Wu, Aiping Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking |
title | Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking |
title_full | Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking |
title_fullStr | Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking |
title_full_unstemmed | Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking |
title_short | Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking |
title_sort | web resources for sars-cov-2 genomic database, annotation, analysis and variant tracking |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10222785/ https://www.ncbi.nlm.nih.gov/pubmed/37243244 http://dx.doi.org/10.3390/v15051158 |
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