Abstract
Design of experiments (DoE) is a term used to describe the application of statistical approaches to interrogate the impact of many variables on the performance of a multivariate system. It is commonly used for process optimization in fields such as chemical engineering and material science. Recent advances in the ability to quantitatively control the expression of genes in biological systems open up the possibility to apply DoE for genetic optimization. In this review targeted to genetic and metabolic engineers, we introduce several approaches in DoE at a high level and describe instances wherein these were applied to interrogate or optimize engineered genetic systems. We discuss the challenges of applying DoE and propose strategies to mitigate these challenges.
Original language | English (US) |
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Article number | kuae010 |
Journal | Journal of Industrial Microbiology and Biotechnology |
Volume | 51 |
DOIs | |
State | Published - 2024 |
Bibliographical note
Publisher Copyright:© 2024 Oxford University Press. All rights reserved.
Keywords
- Design of experiments
- Gene expression
- Metabolic engineering
PubMed: MeSH publication types
- Review
- Journal Article