ReviewBiochemical Society transactions2015
Genome-scale modelling of microbial metabolism with temporal and spatial resolution.
Review in Biochemical Society transactions, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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.
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Who cites it
13 citing papers in PubMed.
- Advances in Machine Learning Models for Predicting Enzyme Kinetic Parameters.Journal of chemical information and modeling · 2026Review
- Artificial intelligence applications in biofilm research: computational approaches for biofilm analysis and antimicrobial prediction.Frontiers in microbiology · 2026Review
- Perspectives on current and future yeast technologies for ethanol-based biofuels and bioproducts.FEMS yeast research · 2025Review
- Discretised Flux Balance Analysis for Reaction-Diffusion Simulation of Single-Cell Metabolism.Bulletin of mathematical biology · 2024Article
- Review
- Revealing the Metabolic Alterations during Biofilm Development ofMetabolites · 2021Article
- Artificial consortium demonstrates emergent properties of enhanced cellulosic-sugar degradation and biofuel synthesis.NPJ biofilms and microbiomes · 2020Article
- Genome-scale reconstruction of Paenarthrobacter aurescens TC1 metabolic model towards the study of atrazine bioremediation.Scientific reports · 2020Article
- The best models of metabolism.Wiley interdisciplinary reviews. Systems biology and medicine · 2017Review
- Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth.Proceedings of the National Academy of Sciences of the United States of America · 2017Article
- Diet shifts provoke complex and variable changes in the metabolic networks of the ruminal microbiome.Microbiome · 2017Article
- Metabolic modeling of a chronic wound biofilm consortium predicts spatial partitioning of bacterial species.BMC systems biology · 2016Article
- Toward Multiscale Models of Cyanobacterial Growth: A Modular Approach.Frontiers in bioengineering and biotechnology · 2016Review
Corrections and comments
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Authors and funding
1 author.
Funding
Abstract
Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated.
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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.