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了基因组数据作为大数据不可或缺的组成部分的激增。大量基因组数据和更复杂的基因组分析技术的可用性促进了基因组学从实验室到临床环境的转变。更全面，更精确的DNA测序使患者能够在分子水平上解决健康问题。促进早期诊断，及时干预,和个性化的医疗保健管理策略。通过鉴定相关基因进一步探索疾病机制可能有助于发现治疗靶标。对个体疾病风险的预测允许改进分层和个性化预防措施。鉴于大量的基因组数据，人工智能,作为一种新兴的数据分析技术，有望对基因组学产生重大影响。
