Food-derived bioactive peptides, as potential ingredients in health-promoting functional foods targeting diet-related chronic diseases, have attracted increasing attention because of their high biological activities, low toxicity, and easy of metabolism in human body. However, conventional methods for analyzing the bioactive peptides are not only expensive but also time-consuming; these drawbacks limited detailed studies and rapid development of bioactive peptides. Emerging bioinformatics approaches may overcome these problems to enable bioactive peptide research. The aim of this review is to provide an overview of research progress in the bioinformatics methods used for identifying, characterizing, elaborating bioactive mechanisms of, and producing food-derived bioactive peptides, and also to present an effective workflow. The workflow has been integrated in silico and traditional methods to predict, validate, and modify bioactive peptides.

食品来源的生物活性肽作为针对饮食相关慢性疾病的健康功能食品的潜在成分，由于它们的高生物活性，低毒性和在人体中的新陈代谢而受到了越来越多的关注。然而，用于分析生物活性肽的常规方法不仅昂贵而且耗时。这些缺点限制了生物活性肽的详细研究和快速发展。新兴的生物信息学方法可以克服这些问题，从而实现生物活性肽的研究。这篇综述的目的是概述生物信息学方法的研究进展，该方法用于鉴定，表征，拟订食品来源的生物活性肽的生物活性机制，并生产食品衍生的生物活性肽，并提出一种有效的工作流程。在计算机和传统方法中预测，验证和修饰生物活性肽。