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大数据时代转化医学中基因组数据的应用

Application of Genomic Data in Translational Medicine During the Big Data Era.

机构信息

Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, 210029 Nanjing, Jiangsu, China.

Department of Neonatology, Obstetrics and Gynecology Hospital of Fudan University, 200090 Shanghai, China.

出版信息

Front Biosci (Landmark Ed). 2024 Jan 12;29(1):7. doi: 10.31083/j.fbl2901007.

Abstract

Advances in gene sequencing technology and decreasing costs have resulted in a proliferation of genomic data as an integral component of big data. The availability of vast amounts of genomic data and more sophisticated genomic analysis techniques has facilitated the transition of genomics from the laboratory to clinical settings. More comprehensive and precise DNA sequencing empowers patients to address health issues at the molecular level, facilitating early diagnosis, timely intervention, and personalized healthcare management strategies. Further exploration of disease mechanisms through identification of associated genes may facilitate the discovery of therapeutic targets. The prediction of an individual's disease risk allows for improved stratification and personalized prevention measures. Given the vast amount of genomic data, artificial intelligence, as a burgeoning technology for data analysis, is poised to make a significant impact in genomics.

摘要

基因测序技术的进步和成本的降低导致基因组数据呈指数级增长,成为大数据的一个组成部分。大量基因组数据的可用性和更复杂的基因组分析技术促进了基因组学从实验室向临床环境的转变。更全面和精确的 DNA 测序使患者能够在分子水平上解决健康问题,有助于早期诊断、及时干预和个性化的医疗保健管理策略。通过识别相关基因来进一步探索疾病机制,可能有助于发现治疗靶点。预测个体的疾病风险可以改善分层和个性化的预防措施。鉴于基因组数据的庞大数量,人工智能作为数据分析的新兴技术,有望在基因组学领域产生重大影响。

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