江海平,高纯纯,刘文豪,杨运桂,李鑫.数据驱动的生命科学研究进展[J].中国科学院院刊,2024,39(5):862-871.

数据驱动的生命科学研究进展

Advances in data-driven life sciences research

江海平^1,2
中国科学院动物研究所 北京 100101;北京干细胞与再生医学研究院 北京 100101
JIANG Haiping^1,2
Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China;Beijing Institute for Stem Cell and Regenerative Medicine, Chinese Academy of Sciences, Beijing 100101, China
高纯纯³
国家生物信息中心 北京 100101
GAO Chunchun³
China National Center for Bioinformation, Beijing 100101, China
刘文豪^1,2
中国科学院动物研究所 北京 100101;北京干细胞与再生医学研究院 北京 100101
LIU Wenhao^1,2
Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China;Beijing Institute for Stem Cell and Regenerative Medicine, Chinese Academy of Sciences, Beijing 100101, China
杨运桂³
国家生物信息中心 北京 100101
YANG Yungui³
China National Center for Bioinformation, Beijing 100101, China
李鑫^1,2*
中国科学院动物研究所 北京 100101;北京干细胞与再生医学研究院 北京 100101
LI Xin^1,2*
Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China;Beijing Institute for Stem Cell and Regenerative Medicine, Chinese Academy of Sciences, Beijing 100101, China

         科学研究范式|大数据|生命科学

        scientific paradigm|big-data|life science

        生命科学发展日新月异，伴随着大量实验技术的更新，生物大数据逐渐产生并在生命科学研究中扮演着日益重要的角色。首先，生物大数据具有多样性和复杂性，包括基因组数据、表观基因组数据、蛋白质组数据等多种类型。这些数据为研究人员提供了更全面的信息，有助于揭示生命现象背后的规律。其次，数据驱动的生命科学新发展和应用涵盖了基因编辑、精准医疗、药物研发等诸多领域，为人类健康和生命质量提供了前所未有的可能性。然而，生命科学研究大数据时代也面临着包括数据存储、数据共享、隐私保护等多方面的问题，以及如何将海量数据转化为可靠的科学发现等挑战。文章简要概括了生物数据推动生命科学的发展规律，梳理了生物大数据组成、特点及来源，阐述并讨论了数据驱动的生命科学研究新范式下的共性问题和我国面临的挑战。

        The field of life sciences is rapidly evolving, driven by advancements in experimental techniques and vast biological big data which gradually arise and play an increasingly important role in life science research. First of all, biological big data has diversity and complexity, including genomic data, epigenomic data, proteomic data and other types. These data provide researchers with more comprehensive information and help reveal the laws behind life phenomena. Second, new data-driven developments and applications in life sciences cover many fields such as gene editing, precision medicine, drug development, etc., providing unprecedented possibilities for human health and quality of life. However, the era of big data for life science research also faces challenges in various aspects including data storage, sharing, and privacy protection, as well as how to transform massive data into reliable scientific discoveries. This paper provides a brief overview of the law of development of biological data in driving life sciences, sorts out the composition and characteristics of biological big data and its sources, as well as elaborates and discusses the common problems and challenges faced by our country under the new paradigm of data-driven life science research.