ReviewJournal of industrial microbiology & biotechnology2015
Applications of genome-scale metabolic network model in metabolic engineering.
Review in Journal of industrial microbiology & biotechnology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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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.
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Who cites it
34 citing papers in PubMed.
- A multi-way SMILES-based hypergraph inference network for metabolic model reconstruction.Communications biology · 2026Article
- IGM: Integrated Gene-expression Modeling for multi-condition flux-preserving genome-scale metabolic models.PloS one · 2026Article
- Development and application of synthetic biology tools for improved production of human breast milk components.Synthetic and systems biotechnology · 2025Review
- RSEA: A Web Server for Pathway Enrichment Analysis of Metabolic Reaction Sets.Biotechnology and bioengineering · 2025Article
- Metabolic network reconstruction as a resource for analyzing Salmonella Typhimurium SL1344 growth in the mouse intestine.PLoS computational biology · 2025Article
- Integrating Genome-Scale Metabolic Models with Patient Plasma Metabolome to Study Endothelial Metabolism In Situ.International journal of molecular sciences · 2024Article
- Current advances for omics-guided process optimization of microbial manufacturing.Bioresources and bioprocessing · 2023Review
- Stable isotope-assisted metabolite profiling reveals new insights into L-tryptophan chemotrophic metabolism of Rubrivivax benzoatilyticus.World journal of microbiology & biotechnology · 2023Article
- Genome-Scale Modeling and Systems Metabolic Engineering of Vibrio natriegens for the Production of 1,3-Propanediol.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Elucidating the impact ofFrontiers in plant science · 2023Article
- Systematizing Microbial Bioplastic Production for Developing Sustainable Bioeconomy: Metabolic Nexus Modeling, Economic and Environmental Technologies Assessment.Journal of polymers and the environment · 2023Review
- A workflow for annotating the knowledge gaps in metabolic reconstructions using known and hypothetical reactions.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- In silico-guided metabolic engineering of Bacillus subtilis for efficient biosynthesis of purine nucleosides by blocking the key backflow nodes.Biotechnology for biofuels and bioproducts · 2022Article
- Integrating Systems and Synthetic Biology to Understand and Engineer Microbiomes.Annual review of biomedical engineering · 2021Review
- Alternative Strategies for Microbial Remediation of Pollutants via Synthetic Biology.Frontiers in microbiology · 2020Review
- Current status and applications of genome-scale metabolic models.Genome biology · 2019Review
- New Applications of Synthetic Biology Tools for Cyanobacterial Metabolic Engineering.Frontiers in bioengineering and biotechnology · 2019Review
- CiliateGEM: an open-project and a tool for predictions of ciliate metabolic variations and experimental condition design.BMC bioinformatics · 2018Article
- Development and validation of an updated computational model of Streptomyces coelicolor primary and secondary metabolism.BMC genomics · 2018Article
- In silico engineering ofPeerJ · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome-scale metabolic network model (GEM) is a fundamental framework in systems metabolic engineering. GEM is built upon extensive experimental data and literature information on gene annotation and function, metabolites and enzymes so that it contains all known metabolic reactions within an organism. Constraint-based analysis of GEM enables the identification of phenotypic properties of an organism and hypothesis-driven engineering of cellular functions to achieve objectives. Along with the advances in omics, high-throughput technology and computational algorithms, the scope and applications of GEM have substantially expanded. In particular, various computational algorithms have been developed to predict beneficial gene deletion and amplification targets and used to guide the strain development process for the efficient production of industrially important chemicals. Furthermore, an Escherichia coli GEM was integrated with a pathway prediction algorithm and used to evaluate all possible routes for the production of a list of commodity chemicals in E. coli. Combined with the wealth of experimental data produced by high-throughput techniques, much effort has been exerted to add more biological contexts into GEM through the integration of omics data and regulatory network information for the mechanistic understanding and improved prediction capabilities. In this paper, we review the recent developments and applications of GEM focusing on the GEM-based computational algorithms available for microbial metabolic engineering.
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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.