ArticleFrontiers in cell and developmental biology2015
RobOKoD: microbial strain design for (over)production of target compounds.
Article in Frontiers in cell and developmental biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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Who cites it
10 citing papers in PubMed.
- Article
- OptCouple: Joint simulation of gene knockouts, insertions and medium modifications for prediction of growth-coupled strain designs.Metabolic engineering communications · 2019Article
- Data Management in Computational Systems Biology: Exploring Standards, Tools, Databases, and Packaging Best Practices.Methods in molecular biology (Clifton, N.J.) · 2019Article
- OptPipe - a pipeline for optimizing metabolic engineering targets.BMC systems biology · 2017Article
- Metabolic modeling to identify engineering targets for Komagataella phaffii: The effect of biomass composition on gene target identification.Biotechnology and bioengineering · 2017Article
- Selection Finder (SelFi): A computational metabolic engineering tool to enable directed evolution of enzymes.Metabolic engineering communications · 2017Article
- SYNBIOCHEM Synthetic Biology Research Centre, Manchester - A UK foundry for fine and speciality chemicals production.Synthetic and systems biotechnology · 2016Article
- Bioinformatics for the synthetic biology of natural products: integrating across the Design-Build-Test cycle.Natural product reports · 2016Review
- Editorial: Current Challenges in Modeling Cellular Metabolism.Frontiers in bioengineering and biotechnology · 2015Article
- Model validation and selection in metabolic flux analysis and flux balance analysis.Biotechnology progressReview
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sustainable production of target compounds such as biofuels and high-value chemicals for pharmaceutical, agrochemical, and chemical industries is becoming an increasing priority given their current dependency upon diminishing petrochemical resources. Designing these strains is difficult, with current methods focusing primarily on knocking-out genes, dismissing other vital steps of strain design including the overexpression and dampening of genes. The design predictions from current methods also do not translate well-into successful strains in the laboratory. Here, we introduce RobOKoD (Robust, Overexpression, Knockout and Dampening), a method for predicting strain designs for overproduction of targets. The method uses flux variability analysis to profile each reaction within the system under differing production percentages of target-compound and biomass. Using these profiles, reactions are identified as potential knockout, overexpression, or dampening targets. The identified reactions are ranked according to their suitability, providing flexibility in strain design for users. The software was tested by designing a butanol-producing Escherichia coli strain, and was compared against the popular OptKnock and RobustKnock methods. RobOKoD shows favorable design predictions, when predictions from these methods are compared to a successful butanol-producing experimentally-validated strain. Overall RobOKoD provides users with rankings of predicted beneficial genetic interventions with which to support optimized strain design.
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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.