ArticleGenome research2007
Evaluation of predicted network modules in yeast metabolism using NMR-based metabolite profiling.
Article in Genome research, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- QTL mapping of modelled metabolic fluxes reveals gene variants impacting yeast central carbon metabolism.Scientific reports · 2020Article
- The landscape of tiered regulation of breast cancer cell metabolism.Scientific reports · 2019Article
- Diversity of flux distribution in central carbon metabolism of S. cerevisiae strains from diverse environments.Microbial cell factories · 2016Article
- Quantitative assessment of gene expression network module-validation methods.Scientific reports · 2015Article
- Metabolic Impacts of Using Nitrogen and Copper-Regulated Promoters to Regulate Gene Expression in Neurospora crassa.G3 (Bethesda, Md.) · 2015Article
- Cold adaptation shapes the robustness of metabolic networks in Drosophila melanogaster.Evolution; international journal of organic evolution · 2014Article
- Prolonged antibiotic use induces intestinal injury in mice that is repaired after removing antibiotic pressure: implications for empiric antibiotic therapy.Metabolomics : Official journal of the Metabolomic Society · 2014Article
- Metabolite profiling to characterize disease-related bacteria: gluconate excretion by Pseudomonas aeruginosa mutants and clinical isolates from cystic fibrosis patients.The Journal of biological chemistry · 2013Article
- Purification of transcripts and metabolites from Drosophila heads.Journal of visualized experiments : JoVE · 2013Article
- FOCAL: an experimental design tool for systematizing metabolic discoveries and model development.Genome biology · 2012Article
- Flux variability scanning based on enforced objective flux for identifying gene amplification targets.BMC systems biology · 2012Article
- F2C2: a fast tool for the computation of flux coupling in genome-scale metabolic networks.BMC bioinformatics · 2012Article
- Metabolic Profiling Comparison of Human Pancreatic Ductal Epithelial Cells and Three Pancreatic Cancer Cell Lines using NMR Based Metabonomics.Journal of molecular biomarkers & diagnosis · 2012Article
- Stitching together multiple data dimensions reveals interacting metabolomic and transcriptomic networks that modulate cell regulation.PLoS biology · 2012Article
- Article
- Projection to latent pathways (PLP): a constrained projection to latent variables (PLS) method for elementary flux modes discrimination.BMC systems biology · 2011Article
- IQMNMR: Open source software using time-domain NMR data for automated identification and quantification of metabolites in batches.BMC bioinformatics · 2011Article
- Metabolite extraction from suspension-cultured mammalian cells for global metabolite profiling.Nature protocols · 2011Article
- FFCA: a feasibility-based method for flux coupling analysis of metabolic networks.BMC bioinformatics · 2011Article
- An integrated approach to characterize genetic interaction networks in yeast metabolism.Nature genetics · 2011Article
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9 authors.
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Abstract
Genome-scale metabolic models promise important insights into cell function. However, the definition of pathways and functional network modules within these models, and in the biochemical literature in general, is often based on intuitive reasoning. Although mathematical methods have been proposed to identify modules, which are defined as groups of reactions with correlated fluxes, there is a need for experimental verification. We show here that multivariate statistical analysis of the NMR-derived intra- and extracellular metabolite profiles of single-gene deletion mutants in specific metabolic pathways in the yeast Saccharomyces cerevisiae identified outliers whose profiles were markedly different from those of the other mutants in their respective pathways. Application of flux coupling analysis to a metabolic model of this yeast showed that the deleted gene in an outlying mutant encoded an enzyme that was not part of the same functional network module as the other enzymes in the pathway. We suggest that metabolomic methods such as this, which do not require any knowledge of how a gene deletion might perturb the metabolic network, provide an empirical method for validating and ultimately refining the predicted network structure.
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