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学科交叉背景下人工智能融入《合成生物学》教学的设计与实践

[Design and practice of integrating artificial intelligence into the teaching of "Synthetic Biology" under the background of discipline crossing].

作者信息

Wang Kai, Luan Xiaoli, Zhou Jingwen

机构信息

School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, Jiangsu, China.

School of Biotechnology, Jiangnan University, Wuxi 214122, Jiangsu, China.

出版信息

Sheng Wu Gong Cheng Xue Bao. 2024 Sep 25;40(9):3282-3295. doi: 10.13345/j.cjb.240317.

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.

摘要

近年来,人工智能已被用于赋能合成生物学,在蛋白质结构的模拟与预测以及调控元件和代谢网络的设计与优化方面展现出巨大潜力。将人工智能融入合成生物学教学符合合成生物学的发展趋势,能够促进跨学科高层次人才的培养和协同创新。本文从建立跨学科课程内容和教学方法、兼顾人工智能在合成生物学中的基础与应用、培养自主学习和创新实践能力以及加强人工智能相关伦理教育等方面阐述了将人工智能融入合成生物学教学的思路。此外,设计了一个将人工智能与合成生物学教学内容相结合的体系,重点在于补充人工智能基础知识并将其融入合成生物学的课堂教学和实验教学内容。再者,以江南大学的合成生物学课程为例,介绍了在学科交叉背景下将人工智能融入该课程教学的途径。最后,对教学效果进行了展望。

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