{"title":"Machine Learning Empowering Microbial Cell Factory: A Comprehensive Review.","authors":"Dechun Kong, Jinyi Qian, Cong Gao, Yuetong Wang, Tianqiong Shi, Chao Ye","doi":"10.1007/s12010-025-05260-x","DOIUrl":null,"url":null,"abstract":"<p><p>The wide application of machine learning has provided more possibilities for biological manufacturing, and the combination of machine learning and synthetic biology technology has ignited even more brilliant sparks, which has created an unpredictable value for the upgrading of microbial cell factories. The review delves into the synergies between machine learning and synthetic biology to create research worth investigating in biotechnology. We explore relevant databases, toolboxes, and machine learning-derived models. Furthermore, we examine specific applications of this combined approach in chemical production, human health, and environmental remediation. By elucidating these successful integrations, this review aims to provide valuable guidance for future research at the intersection of biomanufacturing and artificial intelligence.</p>","PeriodicalId":465,"journal":{"name":"Applied Biochemistry and Biotechnology","volume":" ","pages":""},"PeriodicalIF":3.3000,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Biochemistry and Biotechnology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s12010-025-05260-x","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The wide application of machine learning has provided more possibilities for biological manufacturing, and the combination of machine learning and synthetic biology technology has ignited even more brilliant sparks, which has created an unpredictable value for the upgrading of microbial cell factories. The review delves into the synergies between machine learning and synthetic biology to create research worth investigating in biotechnology. We explore relevant databases, toolboxes, and machine learning-derived models. Furthermore, we examine specific applications of this combined approach in chemical production, human health, and environmental remediation. By elucidating these successful integrations, this review aims to provide valuable guidance for future research at the intersection of biomanufacturing and artificial intelligence.
期刊介绍:
This journal is devoted to publishing the highest quality innovative papers in the fields of biochemistry and biotechnology. The typical focus of the journal is to report applications of novel scientific and technological breakthroughs, as well as technological subjects that are still in the proof-of-concept stage. Applied Biochemistry and Biotechnology provides a forum for case studies and practical concepts of biotechnology, utilization, including controls, statistical data analysis, problem descriptions unique to a particular application, and bioprocess economic analyses. The journal publishes reviews deemed of interest to readers, as well as book reviews, meeting and symposia notices, and news items relating to biotechnology in both the industrial and academic communities.
In addition, Applied Biochemistry and Biotechnology often publishes lists of patents and publications of special interest to readers.