Metabolomics in the Era of Artificial Intelligence

Elizabeth A Coler, Wunxuan Chen, Alexey V Melnik, James T Morton, Alexander A Aksenov
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Abstract

Artificial Intelligence (AI) is rapidly revolutionizing our daily lives, as it automates mundane tasks, enhances productivity, and transforms how we interact with technology. We believe it is inevitable that AI will soon become a crucial tool in common research practices, from data analysis to writing papers. Here we explore how this transition is occurring in the field of mass spectrometry-based metabolomics, a rapidly growing area of science. Metabolomics focuses on studying small molecules in biological systems, offering valuable insights into metabolic processes and their impact on health, diseases, and physiological conditions. With the remarkable advancements in sequencing technologies and the exploration of the microbiome, the combination of sequencing and metabolomics presents profound opportunities to understand biological complexity. Incorporating AI will unlock new possibilities and will, in all likelihood, contribute to scientific discoveries in the future. In this review we discuss the current role of AI in metabolomics. Existing practices are examined and we also provide a perspective on future directions for integrating AI into scientific research.
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人工智能时代的代谢组学
人工智能(AI)正在迅速彻底改变我们的日常生活,因为它能将平凡的任务自动化,提高生产率,并改变我们与技术的交互方式。我们相信,人工智能将不可避免地很快成为从数据分析到撰写论文等常见研究实践中的重要工具。在这里,我们将探讨这一转变是如何在基于质谱的代谢组学领域发生的,这是一个快速发展的科学领域。代谢组学侧重于研究生物系统中的小分子,为了解代谢过程及其对健康、疾病和生理状况的影响提供宝贵的见解。随着测序技术的显著进步和对微生物组的探索,测序与代谢组学的结合为了解生物的复杂性提供了深远的机遇。结合人工智能将开启新的可能性,并很有可能在未来为科学发现做出贡献。在本综述中,我们将讨论人工智能目前在代谢组学中的作用。我们研究了现有的做法,并对将人工智能融入科学研究的未来方向提出了展望。
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