多学科交叉背景下人工智能融入“合成生物学”课程教学的设计与实践
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江南大学“轻工技术与工程”双一流学科与支撑学科协同发展支持计划(QGJC20230102)


Design and practice of integrating artificial intelligence into the teaching of “Synthetic Biology” under the background of discipline crossing
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    摘要:

    近年来,人工智能赋能合成生物学迅速发展,特别是在蛋白质结构模拟与预测、调控元件与代谢网络设计与优化等方面展现了巨大的潜力。加强人工智能融入“合成生物学”课程的教学,顺应合成生物学前沿发展趋势,将有效推动多学科高水平复合型人才培养与协同创新。本文从构建多学科融合的课程内容体系与教学模式、兼顾人工智能基础及其在合成生物学的应用、培养自主学习与创新实践能力、加强人工智能相关的科技伦理教育等方面,阐述了人工智能融入“合成生物学”课程的教学理念。在此基础上,从人工智能基础的补充、人工智能融入“合成生物学”的课堂教学内容、人工智能融入实验教学内容这三个方面,设计了人工智能与“合成生物学”课程内容融合的体系。进而结合教学理念与内容构设,并以江南大学“合成生物学”课程为例,阐述了多学科交叉背景下人工智能融入课程的建设路径。最后,对于教学的预期成效进行了展望。

    Abstract:

    In recent years, artificial intelligence has been employed to empower synthetic biology, demonstrating great potential in the simulation and prediction of protein structures as well as the design and optimization of regulatory elements and metabolic networks. Integrating artificial intelligence into the teaching of Synthetic Biology is in line with the development trends of synthetic biology and can promote the cultivation of interdisciplinary high-level talents and collaborative innovation. This paper expounds the idea of integrating artificial intelligence into the teaching of Synthetic Biology from establishing interdisciplinary course contents and teaching methods, simultaneously considering the fundamentals and application of artificial intelligence in synthetic biology, cultivating independent learning and innovative practice abilities, and enhancing the ethics education related to artificial intelligence. Furthermore, a system integrating artificial intelligence with the teaching contents of Synthetic Biology is designed, which focuses on supplementing fundamentals of artificial intelligence and incorporating artificial intelligence into the classroom and experimental teaching contents of Synthetic Biology. Moreover, with the course of Synthetic Biology in Jiangnan University as an example, this paper presents the pathway of integrating artificial intelligence into the teaching of this course under the background of discipline crossing. Finally, the teaching effects are expected.

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王锴,栾小丽,周景文. 多学科交叉背景下人工智能融入“合成生物学”课程教学的设计与实践[J]. 生物工程学报, 2024, 40(9): 3282-3295

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  • 收稿日期:2024-04-11
  • 最后修改日期:2024-06-05
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  • 在线发布日期: 2024-09-24
  • 出版日期: 2024-09-25
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