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[Databases, knowledge bases, and large models for biomanufacturing].

Zhitao Mao1,2, Xiaoping Liao1,2, Hongwu Ma1,2

  • 1Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.

Sheng Wu Gong Cheng Xue Bao = Chinese Journal of Biotechnology
|April 2, 2025
PubMed
Summary
This summary is machine-generated.

Biomanufacturing uses biology and engineering for sustainable production, reducing emissions and costs. The integration of AI and large models is driving this field into a data-driven era.

Keywords:
biomanufacturingdata-drivendatabasesknowledge baseslarge models

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Area of Science:

  • Biotechnology and Biomanufacturing
  • Computational Biology
  • Chemical Engineering

Background:

  • Biomanufacturing offers sustainable alternatives to petrochemical processes, reducing CO2 emissions and costs.
  • Advancements in systems biology, synthetic biology, and bioinformatics are key drivers.
  • The integration of information technology is transforming biomanufacturing into a data-driven industry.

Purpose of the Study:

  • To review recent advancements in biomanufacturing databases, knowledge bases, and large language models.
  • To explore future development directions and emerging technical methods in data-driven biomanufacturing.
  • To provide guidance for scientific research in biomanufacturing.

Main Methods:

  • Literature review of databases, knowledge bases, and large language models in biomanufacturing.
  • Analysis of the integration of artificial intelligence, large models, and high-performance computing with biotechnology.
  • Exploration of challenges and emerging technical methods in the field.

Main Results:

  • Significant progress has been made in developing specialized databases and knowledge bases for biomanufacturing.
  • Large language models are increasingly being applied to analyze biological data and optimize biomanufacturing processes.
  • The convergence of AI and biotechnology is accelerating innovation and efficiency.

Conclusions:

  • Data-driven approaches, powered by AI and large models, are revolutionizing biomanufacturing.
  • Continued research in databases, knowledge bases, and AI integration is crucial for future advancements.
  • Biomanufacturing holds significant potential for sustainable and cost-effective production.