Article(id=1242141240716763266, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242141225407558554, articleNumber=null, orderNo=null, doi=10.3981/j.issn.1000-7857.2024.05.00538, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1714233600000, receivedDateStr=2024-04-28, revisedDate=1718035200000, revisedDateStr=2024-06-11, acceptedDate=null, acceptedDateStr=null, onlineDate=1720454400000, onlineDateStr=2024-07-09, pubDate=1719504000000, pubDateStr=2024-06-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1720454400000, onlineIssueDateStr=2024-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774079149653, creator=sys-migrate, updateTime=1774079149653, updator=sys-migrate, issue=Issue{id=1242141225407558554, tenantId=1146029695717560320, journalId=1146031591421210625, year='2024', volume='42', issue='12', pageStart='1', pageEnd='200', issueExtLink='null', onlineDate='null', pubDate='1719504000000', pubDateStr='2024-06-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=null, issueType=-1, specialIssue=null, createTime=1774079145994, creator='sys-migrate', updateTime=1774079145994, updator='sys-migrate', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=51, endPage=74, ext={EN=ArticleExt(id=1242141244172874726, articleId=1242141240716763266, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Multi-omics big data and medical advancements, columnId=1242141235033481325, journalTitle=Science & Technology Review, columnName=Exclusive：Foster New Quality Productive Forces to Strengthen High-Level Science and Technology Self-Reliance, runingTitle=null, highlight=null, articleAbstract=Advances in multi-omics technologies, cohort study design, data science, and machine learning are transforming evidence-based medicine, offering a promising outlook for the future of next-generation "deep" medicine. We hereby summarized the development trends in multi-omics experimental techniques, including genomics and epigenomics sequencing, transcriptomics and single-cell transcriptomics, proteomics, metabolomics, microbiomics, imaging, and biosensors. Furthermore, we introduced progress in big data analysis methods such as genome-wide association studies, interpretation of genome-wide association signals, polygenic risk scoring, Mendelian randomization, and artificial intelligence algorithms. Additionally, we discussed the clinical applications of these technologies in disease subtyping, diagnosis and prediction, drug development, and clinical trial design. Finally, we discussed the challenges faced and explored future directions in cohort study design, data management and sharing, and the enhancement of international collaboration., authors=LIU Siyang¹, LIN Xingchen¹, CHENG Si², WANG Chaolong³, LI Hao², authorsList=LIU Siyang, LIN Xingchen, CHENG Si, WANG Chaolong, LI Hao, authorCompany=1. School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen 518107, China;
2. China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China;
3. School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1242141243627615196, articleId=1242141240716763266, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=多组学大数据与医学发展, columnId=1242141234844737642, journalTitle=科技导报, columnName=专题：培育新质生产力 助力高水平科技自立自强, runingTitle=null, highlight=null, articleAbstract=多组学技术、队列研究设计、数据科学和机器学习的进步已经开始改变循证医学，为下一代“深度”医学的未来提供了诱人的前景。总结了基因组与基因组修饰测序、转录组与单细胞转录组、蛋白组、代谢组、微生物组、影像组与生物传感器等多组学实验技术和全基因组关联分析、全基因组关联信号解读、多基因风险评分、孟德尔随机化与人工智能算法等大数据分析技术的发展趋势，探讨了这些技术在疾病分型、诊断与预测、药物研发和临床试验设计等方面的临床应用。针对多组学大数据与医学发展面临的挑战，展望了未来队列设计、数据管理与共享、国际合作等发展方向。, authors=刘斯洋¹, 林星辰¹, 程丝², 王超龙³, 李昊², authorsList=刘斯洋, 林星辰, 程丝, 王超龙, 李昊, authorCompany=1. 中山大学公共卫生学院(深圳), 深圳 518107;
2. 首都医科大学附属北京天坛医院, 国家神经系统疾病临床医学研究中心, 北京 100070;
3. 华中科技大学公共卫生学院, 武汉 430030, correspAuthors=null, authorNote=刘斯洋，副教授，研究方向为医学遗传学方法研发与应用，电子信箱：liusy99@mail.sysu.edu.cn；李昊（通信作者），教授，研究方向为临床流行病方法学，电子信箱：lihao@ncrcnd.org.cn, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=0OR2zzunM5GaL6a3dQoFWg==, pdfFileSize=1573869, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=国家重点研发计划项目（2022YFC2502400）)}, authors=null, keywords=[Keyword(id=1242141242797142995, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1242141240716763266, language=CN, orderNo=1, keyword=多组学), Keyword(id=1242141242868446165, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1242141240716763266, language=CN, orderNo=1, keyword=大数据), 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