Biofuser:一个多源数据融合平台,用于融合发酵过程设备的数据
Dequan Zhang1, Wei Jiang2, Jincheng Lou2
1State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, China.
Frontiers in digital health
|November 5, 2024
概括
一个新的平台,Biofuser,整合了各种生物工艺数据,以提高优化. 这便于机器学习应用,加速智能生物制造和合成生物学工业化.
科学领域:
- 生物技术是生物技术.
- 合成生物学 合成生物学
- 工艺工程是过程工程.
背景情况:
- 传统的生物过程优化落后于合成生物学进步.
- 越来越多地使用先进的传感器产生异质数据,使分析复杂化.
- 需要综合数据解决方案来弥合研究和工业应用之间的差距.
研究的目的:
- 为了介绍Biofuser,一个新的多源数据融合平台.
- 为了使异质生物工艺数据的无集成和处理.
- 支持用于生物过程优化的高级分析,建模和控制.
主要方法:
- 开发一个平台来收集和处理多来源的异质数据.
- 将数据集成到一个统一的格式中,用于可视化,分析和模型构建.
- 为机器学习和深度学习集成提供API.
主要成果:
- 在 рибофлавин发酵过程中证明了成功的应用.
- 启用识别设备故障和关键过程因素.
- 展示了准确预测生物过程的能力.
结论:
- 生物发酵器显著提高了发酵优化技术.
- 该平台是将人工智能集成到生物过程中的关键基础设施.
- 预计将加速智能生物制造的发展.
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