ReviewBiotechnology journal2010
Systems metabolic engineering: genome-scale models and beyond.
Review in Biotechnology journal, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
28 citing papers in PubMed.
- Beyond pigments and perfumes: engineering in the carotenoid and apocarotenoid spectrum, novel enzymes, and synthetic biology strategies.Frontiers in bioengineering and biotechnology · 2025Review
- The Construction of an Extreme Radiation-Resistant Perchlorate-Reducing Bacterium UsingInternational journal of molecular sciences · 2024Article
- A Fermentation State Marker Rule Design Task in Metabolic Engineering.Bioengineering (Basel, Switzerland) · 2023Article
- Construction of cascade circuits for dynamic temporal regulation and its application to PHB production.Biotechnology for biofuels and bioproducts · 2023Article
- Systematizing Microbial Bioplastic Production for Developing Sustainable Bioeconomy: Metabolic Nexus Modeling, Economic and Environmental Technologies Assessment.Journal of polymers and the environment · 2023Review
- Overlapping promoter library designed for rational heterogenous expression in Cordyceps militaris.Microbial cell factories · 2022Article
- Experimentally Validated Reconstruction and Analysis of a Genome-Scale Metabolic Model of an Anaerobic Neocallimastigomycota Fungus.mSystems · 2021Article
- Development of a Genome-Scale Metabolic Model ofFrontiers in bioengineering and biotechnology · 2020Article
- Multiscale Multiobjective Systems Analysis (MiMoSA): an advanced metabolic modeling framework for complex systems.Scientific reports · 2019Article
- Oceans as a Source of Immunotherapy.Marine drugs · 2019Review
- Genomic sequencing, genome-scale metabolic network reconstruction, and in silico flux analysis of the grape endophytic fungus Alternaria sp. MG1.Microbial cell factories · 2019Article
- Prediction of reaction knockouts to maximize succinate production by Actinobacillus succinogenes.PloS one · 2018Article
- Review
- Development of fungal cell factories for the production of secondary metabolites: Linking genomics and metabolism.Synthetic and systems biotechnology · 2017Review
- Synthetic biology and regulatory networks: where metabolic systems biology meets control engineering.Journal of the Royal Society, Interface · 2016Review
- Genome-scale modeling for metabolic engineering.Journal of industrial microbiology & biotechnology · 2015Review
- Analysis of genetic variation and potential applications in genome-scale metabolic modeling.Frontiers in bioengineering and biotechnology · 2015Review
- A multi-tissue genome-scale metabolic modeling framework for the analysis of whole plant systems.Frontiers in plant science · 2015Article
- Engineering Escherichia coli to overproduce aromatic amino acids and derived compounds.Microbial cell factories · 2014Review
- ReacKnock: identifying reaction deletion strategies for microbial strain optimization based on genome-scale metabolic network.PloS one · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The advent of high throughput genome-scale bioinformatics has led to an exponential increase in available cellular system data. Systems metabolic engineering attempts to use data-driven approaches--based on the data collected with high throughput technologies--to identify gene targets and optimize phenotypical properties on a systems level. Current systems metabolic engineering tools are limited for predicting and defining complex phenotypes such as chemical tolerances and other global, multigenic traits. The most pragmatic systems-based tool for metabolic engineering to arise is the in silico genome-scale metabolic reconstruction. This tool has seen wide adoption for modeling cell growth and predicting beneficial gene knockouts, and we examine here how this approach can be expanded for novel organisms. This review will highlight advances of the systems metabolic engineering approach with a focus on de novo development and use of genome-scale metabolic reconstructions for metabolic engineering applications. We will then discuss the challenges and prospects for this emerging field to enable model-based metabolic engineering. Specifically, we argue that current state-of-the-art systems metabolic engineering techniques represent a viable first step for improving product yield that still must be followed by combinatorial techniques or random strain mutagenesis to achieve optimal cellular systems.
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What OpenQuestion holds
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.