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Synthetic biology is an interdisciplinary science that involves using principles from disciplines such as engineering, molecular biology, cell biology, and systems biology. It involves remodeling existing organisms from nature or constructing completely new synthetic organisms for applications such as protein or enzyme production, bioremediation, value-added macromolecule production, and the addition of desirable traits to crops, to name a few.
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人工智能复合规划需要数据和专家知识

Felix Strieth-Kalthoff1,2, Sara Szymkuć3,4, Karol Molga3,4

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科学领域:

  • 有机化学
  • 人工智能
  • 计算化学

背景情况:

  • 人工智能 (AI) 显示出复杂的多步化学合成计划的前景.
  • 与混合方法相比,只有对反应数据进行培训的人工智能合成规划者表现不佳.
  • 由于数据偏差和合成化学的复杂性,现有的人工智能模型面临挑战.

研究的目的:

  • 研究人工智能驱动的有机合成计划停滞的原因.
  • 为开发更有效的人工智能合成规划工具提出新的方向.
  • 强调将领域专业知识纳入人工智能开发的重要性.

主要方法:

  • 对当前人工智能合成规划方法的分析.
  • 检查合成化学数据集中的数据限制和偏差.
  • 混合人工智能专家系统的概念框架.

主要成果:

  • 反应数据不足并不是人工智能合成计划器限制的唯一原因.
  • 特定领域的复杂性和数据偏差显著阻碍了人工智能性能.
  • 结合人工智能和专家知识的混合方法显示出卓越的性能.

结论:

  • 通过合成化学家的知识和推理来增强人工智能的能力至关重要.
  • 最终用户 (化学家) 在人工智能开发中的积极参与至关重要.
  • 弥合算法与化学合成之间的差距需要人类的专业知识.