ArticleBMC bioinformatics2012
F2C2: a fast tool for the computation of flux coupling in genome-scale metabolic networks.
Article in BMC bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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35 citing papers in PubMed.
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- Investigating intestinal epithelium metabolic dysfunction in celiac disease using personalized genome-scale models.BMC medicine · 2025Article
- Article
- Control Theory and Systems Biology: Potential Applications in Neurodegeneration and Search for Therapeutic Targets.International journal of molecular sciences · 2023Review
- On the representativeness and stability of a set of EFMs.Bioinformatics (Oxford, England) · 2023Article
- Relative flux trade-offs and optimization of metabolic network functionalities.Computational and structural biotechnology journal · 2022Article
- Flux Coupling and the Objective Functions' Length in EFMs.Metabolites · 2020Article
- 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
- SWIFTCORE: a tool for the context-specific reconstruction of genome-scale metabolic networks.BMC bioinformatics · 2020Article
- Flux-based hierarchical organization of Escherichia coli's metabolic network.PLoS computational biology · 2020Article
- Network reduction methods for genome-scale metabolic models.Cellular and molecular life sciences : CMLS · 2020Review
- Essential gene prediction using limited gene essentiality information-An integrative semi-supervised machine learning strategy.PloS one · 2020Article
- Metabolic Model of themBio · 2019Article
- Quantitative flux coupling analysis.Journal of mathematical biology · 2019Article
- Evolutionary design principles in metabolism.Proceedings. Biological sciences · 2019Review
- Cellular determinants of metabolite concentration ranges.PLoS computational biology · 2019Article
- Simulation of heterosis in a genome-scale metabolic network provides mechanistic explanations for increased biomass production rates in hybrid plants.NPJ systems biology and applications · 2019Article
- Improving the EFMs quality by augmenting their representativeness in LP methods.BMC systems biology · 2018Article
- Challenges in modeling the human gut microbiome.Nature biotechnology · 2018Article
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4 authors.
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Abstract
backgroundFlux coupling analysis (FCA) has become a useful tool in the constraint-based analysis of genome-scale metabolic networks. FCA allows detecting dependencies between reaction fluxes of metabolic networks at steady-state. On the one hand, this can help in the curation of reconstructed metabolic networks by verifying whether the coupling between reactions is in agreement with the experimental findings. On the other hand, FCA can aid in defining intervention strategies to knock out target reactions.
resultsWe present a new method F2C2 for FCA, which is orders of magnitude faster than previous approaches. As a consequence, FCA of genome-scale metabolic networks can now be performed in a routine manner.
conclusionsWe propose F2C2 as a fast tool for the computation of flux coupling in genome-scale metabolic networks. F2C2 is freely available for non-commercial use at https://sourceforge.net/projects/f2c2/files/.
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