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大数据时代的深渊微生物研究

Hadal microbial research in the age of big data
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摘要 近年来,我国载人、无人深潜技术和深海装备领域的重大突破,使得大范围、系统性地获得深渊沉积物和水体样本成为了可能。以测序技术为代表的多组学技术的大力发展,以及人工智能在生命科学领域的前沿探索,使得深渊微生物的研究迎来了大样本量、大数据量、多数据类型和多学科交叉的大数据时代。充分利用大数据所提供的优势解析深渊微生物所涉及的生物学和生态学科学问题,并进一步通过微生物大数据为海洋学和地球科学提供新的线索,是新时代所面临的关键机遇与挑战。该文对深渊微生物研究的历程与现状进行了小结,并通过对标国际人类微生物组、地球微生物组以及Tara Oceans计划等其他先行的微生物大数据研究范例,对大数据时代开展深渊微生物研究的新思路和新范式进行了梳理和展望。 The recent advances in China's deep-submarine and deep-sea equipment technologies,both manned and unmanned,have made large-scale and systematic collection of hadal sediment and water samples possible.The rapid advancement of multi-omics technology,particularly sequencing technology,and the cutting-edge implementation of artificial intelligence in the life sciences field have inaugurated the big data era.This era encompasses extensive sample sizes,copious amounts of data,diverse data types,and cross-disciplinary research in the study of hadal microorganisms.Making full use of the benefits offered by big data to examine the scientific concerns of biology and ecology related to hadal microorganisms and generating fresh leads for oceanography and earth sciences via microbial big data present vital opportunities and challenges in this new era.Additionally,we analyze and anticipate new concepts and paradigms emerging in the era of big data by comparing them with other pioneering microbial big data research projects,such as the Human Microbiome Project,the Earth Microbiome Project,and the Tara Oceans Program.
作者 王景 赵维殳 肖湘 WANG Jing;ZHAO Wei-Shu;XIAO Xiang(School of Oceanography,Shanghai Jiao Tong University,Shanghai 200030,China;State Key Laboratory of Microbial Metabolism,International Center for Deep Life Investigation(IC-DLI),School of Life Sciences and Biotechnology,Shanghai Jiao Tong University,Shanghai 200240,China;SJTU Yazhou Bay Institute of Deepsea Sci-Tech,Sanya 572024,China)
出处 《生命科学》 CSCD 北大核心 2023年第12期1630-1638,共9页 Chinese Bulletin of Life Sciences
基金 国家重点研发计划(2022YFC2805300,2022YFC2805404) 国家自然科学基金创新研究群体项目(41921006)。
关键词 深渊环境 微生物组 大数据 新技术与新方法 hadal environment microbiome big data new method and technology
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