发起人
合成生物学
计算生物学
代谢工程
功能(生物学)
组分(热力学)
生物
计算机科学
基因表达
遗传学
基因
物理
热力学
作者
Andrew P. Cazier,John Blazeck
标识
DOI:10.1002/biot.202100239
摘要
Abstract Synthetic biology continues to progress by relying on more robust tools for transcriptional control, of which promoters are the most fundamental component. Numerous studies have sought to characterize promoter function, determine principles to guide their engineering, and create promoters with stronger expression or tailored inducible control. In this review, we will summarize promoter architecture and highlight recent advances in the field, focusing on the novel applications of inducible promoter design and engineering towards metabolic engineering and cellular therapeutic development. Additionally, we will highlight how the expansion of new, machine learning techniques for modeling and engineering promoter sequences are enabling more accurate prediction of promoter characteristics.
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