ReviewJournal of industrial microbiology & biotechnology2024
Using design of experiments to guide genetic optimization of engineered metabolic pathways.
Review in Journal of industrial microbiology & biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Peptide-Based Nanocomplexes Enable Transferrin-Mediated Uptake and p53-Driven Antitumor Activity in 2D and 3D Glioblastoma Models.International journal of molecular sciences · 2026Article
- Article
- Leveraging agricultural waste manipulation using a novel resveratrol-producing endophytic fungus,Frontiers in bioengineering and biotechnology · 2026Article
- Combinatorial engineering pinpoints shikimate pathway bottlenecks in para-aminobenzoic acid production in Pseudomonas putida.Journal of biological engineering · 2025Article
- Assessment of the Biocontrol Efficacy of Silver Nanoparticles Synthesized byLife (Basel, Switzerland) · 2024Article
- Medium optimization to improve growth and iron uptake by Bacillus tequilensis ASFS1 using fractional factorial designs.Scientific reports · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
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. ONE-SENTENCE SUMMARY: This is a review of literature related to applying Design of Experiments for genetic optimization.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.