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病毒变异不断改变病原体特性，对疫苗、抗病毒药物及防控策略构成严峻挑战。尽管高通量测序及GISAID、GenBank等国际数据库提供了丰富数据，但现有研究仍局限于局部或单一变异特征的分析，缺乏跨时空、多维度的系统解析。为此，本文基于“六全一关联”框架构建了病毒变异全景图，通过整合基因组、变异位点、时空分布、变化趋势、临床信息与数据来源，实现对新冠病毒、流感病毒、呼吸道合胞病毒等多种病毒变异全貌的精准刻画，为疫苗研发、流行趋势预测与精准防控提供科学依据。该平台利用机器学习和大数据分析技术，实现多维信息高效关联。展望未来，全景图将借助移动互联网及实时数据传输，实现数据即时更新、自动预警与动态策略调整，进一步推动全球公共卫生防控与健康安全事业的发展。
Abstract：Viral mutations continuously reshape pathogen characteristics, posing substantial challenges to vaccine development, antiviral therapies, and public health strategies. Although high-throughput sequencing and international databases such as GISAID and GenBank provide vast genomic resources, current research often remains limited to isolated or unidimensional analyses, lacking integrated, spatiotemporal, and multi-faceted insights. To address this gap, we developed a panoramic map of viral mutations based on the "Six Completeness and One Correlation" framework. This approach integrates genomic sequences, mutation sites, spatiotemporal distribution, evolutionary trends, clinical data, and data provenance to comprehensively characterize mutation landscapes of viruses such as SARS-CoV-2, influenza virus, and respiratory syncytial virus. The platform supports informed decision-making in vaccine design, outbreak forecasting, and precision prevention through the application of machine learning and big data analytics for efficient multi-dimensional data correlation.Looking forward, the system is designed to support real-time data updates, automated alerts, and adaptive strategy adjustments via mobile internet and live data streaming, offering a powerful tool to enhance global health security and pandemic preparedness.
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基本信息:
DOI：10.13242/j.cnki.bingduxuebao.250052
中图分类号:TP181;TP311.13;R373
引用信息:
[1]王佶,陈操.基于“六全一关联”框架的病毒变异全景图构建与应用[J].病毒学报,2025,41(04):1001-1006.DOI:10.13242/j.cnki.bingduxuebao.250052.
基金信息:
国家重点研发计划（项目号：2023YFC2306000）,题目：重要病毒变异规律和预测预警研究~~
2025-02-14
2025
2025-07-10
2025
1
2025-07-11
2025-07-11
2025-07-11