人工智能在合成生物学的应用
人工智能在合成生物学的应用
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国家重点研发计划“合成生物学专项”项目(2020YFA0908700);国家自然科学基金面上项目(62072315);深圳市孔雀团 队项目(KQTD2015033117210153)

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Application of Artificial Intelligence in Synthetic Biology: A Review
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National Key R&D Program of China (2020YFA0908700); National Natural Science Foundation of China (62072315); Shenzhen Peacock Team Plan (KQTD2015033117210153)

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    摘要:

    生命系统极其复杂,难以精确描述和预测,这给高效设计合成生物系统提出了挑战,故在合 成生物系统构建中往往须进行海量工程试错和优化。近年来,人工智能技术快速发展,其基于海量数 据的持续学习能力和在未知空间的智能探索能力有效契合了当前合成生物学工程化试错平台的需求, 在复杂生物特征的挖掘与生命系统的设计方面具备巨大潜力。该文回顾并总结人工智能在合成元件工 程、线路工程、代谢工程及基因组工程领域的研究进展,并分析和讨论人工智能与合成生物学交叉研 究在数据标准化、平台智能化、实验自动化、预测精准化方面存在的一系列挑战。人工智能和合成生 物学的融合有望给“设计—构建—测试—学习”闭环的全流程带来变革,而孕育“类合成生物学家” 也将反过来引起人工智能技术的飞跃。

    Abstract:

    Living systems are extremely sophisticated and difficult to accurately describe and predict, posing challenges in designing synthetic biological systems. Therefore, massively parallel trial-and-error processes are often required to optimize synthetic biological systems. In recent years, intelligent technology has experienced rapid development and has demonstrated continual learning capacity from massive data and intelligent exploring ability in unknown space, which perfectly meets the needs of the current trial-and error platform of synthetic biology engineering and shows great potential in mining complex biological patterns and in designing biosystems. This article reviews the progresses of applying artificial intelligence (AI) in the fields of synthetic biological parts engineering, circuit engineering, metabolic engineering, and genome engineering. This article also analyzes a series of challenges in data standardization, platform intellectualization, experimental automation, and accurate prediction of cross-over studies between AI and synthetic biology. By solving these challenges, the entire workflow of “design-build-test-learn” in synthetic biology is expected to be revolutionized by AI, and creating an “AI synthetic biologist” would in turn lead to the technological advances in AI.

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引文格式
李敏,林子杰,廖文斌,陈廷柏,李坚强,陈杰,肖敏凤.人工智能在合成生物学的应用 [J].集成技术,2021,10(5):43-56

Citing format
LI Min, LIN Zijie, LIAO Wenbin, CHEN Tingbo, LI Jianqiang, CHEN Jie, XIAO Minfeng. Application of Artificial Intelligence in Synthetic Biology: A Review[J]. Journal of Integration Technology,2021,10(5):43-56

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  • 在线发布日期: 2021-09-15
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