Food and human health are inextricably linked. As such, revolutionary impacts on health have been derived from advances in the production and distribution of food relating to food safety and fortification with micronutrients. During the past two decades, it has become apparent that the human microbiome has the potential to modulate health, including in ways that may be related to diet and the composition of specific foods. Despite the excitement and potential surrounding this area, the complexity of the gut microbiome, the chemical composition of food, and their interplay in situ remains a daunting task to fully understand. However, recent advances in high-throughput sequencing, metabolomics profiling, compositional analysis of food, and the emergence of electronic health records provide new sources of data that can contribute to addressing this challenge. Computational science will play an essential role in this effort as it will provide the foundation to integrate these data layers and derive insights capable of revealing and understanding the complex interactions between diet, gut microbiome, and health. Here, we review the current knowledge on diet-health-gut microbiota, relevant data sources, bioinformatics tools, machine learning capabilities, as well as the intellectual property and legislative regulatory landscape. We provide guidance on employing machine learning and data analytics, identify gaps in current methods, and describe new scenarios to be unlocked in the next few years in the context of current knowledge.

中文翻译：

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计算饮食：饮食、微生物组和健康的计算方法综述。

食品与人类健康密不可分。因此，与食品安全和微量营养素强化相关的食品生产和分配方面的进步对健康产生了革命性影响。在过去的二十年中，人类微生物组具有调节健康的潜力已经变得越来越明显，包括通过可能与饮食和特定食物成分相关的方式。尽管这一领域令人兴奋并具有潜力，但肠道微生物组的复杂性、食物的化学成分以及它们在原位的相互作用仍然是一项艰巨的任务，需要充分了解。然而，高通量测序、代谢组学分析、食物成分分析以及电子健康记录的出现的最新进展提供了新的数据来源，有助于应对这一挑战。计算科学将在这项工作中发挥重要作用，因为它将为整合这些数据层提供基础，并获得能够揭示和理解饮食、肠道微生物组和健康之间复杂相互作用的见解。在这里，我们回顾了当前有关饮食健康肠道微生物群的知识、相关数据源、生物信息学工具、机器学习能力以及知识产权和立法监管环境。我们提供有关使用机器学习和数据分析的指导，找出当前方法中的差距，并描述未来几年在当前知识背景下将解锁的新场景。