ReviewJournal of the Royal Society, Interface2017
Mathematical modelling of microbes: metabolism, gene expression and growth.
Review in Journal of the Royal Society, Interface, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 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.
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.
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Who cites it
24 citing papers in PubMed.
- Antechokinetics, the kinetics of antimicrobial resistance molecules.Frontiers in pharmacology · 2026Review
- Identification of dynamic models of microbial communities: A workflow addressing identifiability and modeling pitfalls.PLoS computational biology · 2025Article
- Global constraint principle for microbial growth laws.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Bioactive exometabolites drive maintenance competition in simple bacterial communities.mSystems · 2024Article
- Predictions of rhizosphere microbiome dynamics with a genome-informed and trait-based energy budget model.Nature microbiology · 2024Article
- A coarse-grained resource allocation model of carbon and nitrogen metabolism in unicellular microbes.Journal of the Royal Society, Interface · 2023Article
- Understanding and application of Bacillus nitrogen regulation: A synthetic biology perspective.Journal of advanced research · 2023Review
- Resource allocation accounts for the large variability of rate-yield phenotypes across bacterial strains.eLife · 2023Article
- Complex and unexpected outcomes of antibiotic therapy against a polymicrobial infection.The ISME journal · 2022Article
- Elementary vectors and autocatalytic sets for resource allocation in next-generation models of cellular growth.PLoS computational biology · 2022Article
- Dimensionless parameter predicts bacterial prodrug success.Molecular systems biology · 2022Article
- Genome-Scale Reconstruction of Microbial Dynamic Phenotype: Successes and Challenges.Microorganisms · 2021Review
- The effect of natural selection on the propagation of protein expression noise to bacterial growth.PLoS computational biology · 2021Article
- gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models.Genome biology · 2021Article
- Searching for principles of microbial physiology.FEMS microbiology reviews · 2020Review
- A mechanism-aware and multiomic machine-learning pipeline characterizes yeast cell growth.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Flux Balance Analysis for Media Optimization and Genetic Targets to Improve Heterologous Siderophore Production.iScience · 2020Article
- An analytical theory of balanced cellular growth.Nature communications · 2020Article
- Elementary Growth Modes provide a molecular description of cellular self-fabrication.PLoS computational biology · 2020Article
- Modelling microbial communities using biochemical resource allocation analysis.Journal of the Royal Society, Interface · 2019Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The growth of microorganisms involves the conversion of nutrients in the environment into biomass, mostly proteins and other macromolecules. This conversion is accomplished by networks of biochemical reactions cutting across cellular functions, such as metabolism, gene expression, transport and signalling. Mathematical modelling is a powerful tool for gaining an understanding of the functioning of this large and complex system and the role played by individual constituents and mechanisms. This requires models of microbial growth that provide an integrated view of the reaction networks and bridge the scale from individual reactions to the growth of a population. In this review, we derive a general framework for the kinetic modelling of microbial growth from basic hypotheses about the underlying reaction systems. Moreover, we show that several families of approximate models presented in the literature, notably flux balance models and coarse-grained whole-cell models, can be derived with the help of additional simplifying hypotheses. This perspective clearly brings out how apparently quite different modelling approaches are related on a deeper level, and suggests directions for further research.
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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.