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GPro: generative AI-empowered toolkit for promoter design.

Haochen Wang1,2,3,4, Qixiu Du1,2,3,4, Ye Wang1,2,3,4

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Generative AI (GenAI) tools can design synthetic promoters, but are often inflexible. We developed GPro, a user-friendly toolkit enabling customized promoter design for diverse biotechnological applications.

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Area of Science:

  • Synthetic Biology
  • Computational Biology
  • Artificial Intelligence

Background:

  • Synthetic promoters with enhanced functionality are vital for biotechnological advancements.
  • Current Generative AI (GenAI) methods for promoter design lack flexibility due to programming framework and task-specific limitations.

Purpose of the Study:

  • To introduce GPro, a user-friendly toolkit integrating advanced GenAI approaches for flexible synthetic promoter design.
  • To provide a standardized pipeline for promoter design, including training, optimization, and evaluation.

Main Methods:

  • Developed GPro, a toolkit incorporating multiple GenAI-powered promoter design strategies.
  • Implemented a standardized pipeline with options for training, optimization, and evaluation.
  • Included detailed demos for reproducing state-of-the-art promoter design pipelines.

Main Results:

  • GPro offers a user-friendly interface accessible to non-AI experts.
  • The toolkit provides flexibility through optional algorithms and customizable pipeline creation.
  • GPro enables researchers to design synthetic promoters tailored to specific biotechnological tasks.

Conclusions:

  • GPro enhances the accessibility and flexibility of GenAI for synthetic promoter design.
  • This toolkit empowers researchers to create novel promoters with improved functionality for various applications.
  • GPro is released as open-source software, promoting wider adoption and development.