In the modern world, technology is at its peak. Different avenues in
programming and technology have been explored for data analysis, automation,
and robotics. Machine learning is key to optimize data analysis, make accurate
predictions, and hasten/improve existing functions. Thus, presently, the field
of machine learning in artificial intelligence is being developed and its uses
in varying fields are being explored. One field in which its uses stand out is
that of microbial biosynthesis. In this paper, a comprehensive overview of the
differing machine learning programs used in biosynthesis is provided, alongside
brief descriptions of the fields of machine learning and microbial biosynthesis
separately. This information includes past trends, modern developments, future
improvements, explanations of processes, and current problems they face. Thus,
this paper's main contribution is to distill developments in, and provide a
holistic explanation of, 2 key fields and their applicability to improve
industry/research. It also highlights challenges and research directions,
acting to instigate more research and development in the growing fields.
Finally, the paper aims to act as a reference for academics performing
research, industry professionals improving their processes, and students
looking to understand the concept of machine learning in biosynthesis.

现今，技术达到了巅峰。探索了不同的编程和技术途径用于数据分析、自动化和机器人技术。机器学习是优化数据分析、进行准确预测以及加快 / 改进现有功能的关键。因此，目前人工智能领域中的机器学习正在发展，并且正在探索它在不同领域的应用。其中一个领域突出的应用是微生物生物合成。本文提供了微生物生物合成中所使用的不同机器学习程序的全面概述，并简要描述了机器学习和微生物生物合成这两个领域。包括过去的趋势、现代的发展、未来的改进、过程的解释以及当前面临的问题。因此，本文的主要贡献是概括这两个关键领域的发展并提供全面的解释，以及它们对于改进工业 / 研究的适用性。它还突出了挑战和研究方向，旨在激发在不断发展的领域中进行更多的研究和发展。最后，本文旨在成为正在进行研究的学者、改进流程的行业专业人员和想要理解生物合成中的机器学习概念的学生的参考资料。