迈向精准医学:治疗COVID-19的组学方法

IF 3.5 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Biosafety and Health Pub Date : 2023-04-01 DOI:10.1016/j.bsheal.2023.01.002
Xiaoping Cen , Fengao Wang , Xinhe Huang , Dragomirka Jovic , Fred Dubee , Huanming Yang , Yixue Li
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引用次数: 4

摘要

2019冠状病毒病(新冠肺炎)大流行对人类社会产生了毁灭性影响。从严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的基因组监测开始,组学技术的发展使人们对复杂的SARS-CoV-2和新冠肺炎有了更清晰的了解。在此,我们回顾了包括基因组学、蛋白质组学、单细胞多组学和临床表型组学在内的组学如何在回答有关新冠肺炎的生物学和临床问题中发挥作用。大规模测序和先进的分析方法有助于发现新冠肺炎,从病毒进化和严重程度风险预测到潜在的治疗方法。奥密克戎将表明,在利用大数据能力和表型细化的情况下,新冠肺炎大流行的精准和全球化预防和医学。此外,通过深度学习模型解码严重急性呼吸系统综合征冠状病毒2型的进化规律,有望预测新的变种,并获得更精确的数据来预测未来的流行病并及时预防。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Towards precision medicine: Omics approach for COVID-19

The coronavirus disease 2019 (COVID-19) pandemic had a devastating impact on human society. Beginning with genome surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the development of omics technologies brought a clearer understanding of the complex SARS-CoV-2 and COVID-19. Here, we reviewed how omics, including genomics, proteomics, single-cell multi-omics, and clinical phenomics, play roles in answering biological and clinical questions about COVID-19. Large-scale sequencing and advanced analysis methods facilitate COVID-19 discovery from virus evolution and severity risk prediction to potential treatment identification. Omics would indicate precise and globalized prevention and medicine for the COVID-19 pandemic under the utilization of big data capability and phenotypes refinement. Furthermore, decoding the evolution rule of SARS-CoV-2 by deep learning models is promising to forecast new variants and achieve more precise data to predict future pandemics and prevent them on time.

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来源期刊
Biosafety and Health
Biosafety and Health Medicine-Infectious Diseases
CiteScore
7.60
自引率
0.00%
发文量
116
审稿时长
66 days
期刊最新文献
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