The Escherichia coli genome-scale metabolic model (GEM) is an exemplar systems biology model for the simulation of cellular metabolism. Experimental validation of model predictions is essential to pinpoint uncertainty and ensure continued development of accurate models. Here, we quantified the accuracy of four subsequent E. coli GEMs using published mutant fitness data across thousands of genes and 25 different carbon sources. This evaluation demonstrated the utility of the area under a precision-recall curve relative to alternative accuracy metrics. An analysis of errors in the latest (iML1515) model identified several vitamins/cofactors that are likely available to mutants despite being absent from the experimental growth medium and highl...
Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks ...
Genome-scale metabolic models (GEMs) computationally describe gene-protein-reaction associations for...
©2003 BioMed Central LtdOne of the challenges for ‘post-genomic’ biology is the integration of data ...
Background: Constraint-based models of Escherichia coli metabolic flux have played a key role in com...
The genome-scale model (GEM) of metabolism in the bacterium Escherichia coli K-12 has been in develo...
Genome-scale metabolic models have been utilized extensively in the study and engineering of the org...
Diverse datasets, including genomic, transcriptomic, proteomic, and metabolomic data are becoming re...
Genome-scale models of metabolism can illuminate the molecular basis of cell phenotypes. Since some ...
Abstract Background Synthetic biology and related techniques enable genome scale high-throughput inv...
Metabolic models are useful for a number of applications in the world of biology. If one understands...
Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks ...
Genome-scale metabolic modeling is an important tool in the study of metabolism by enhancing the col...
Genome‐scale metabolic models (GEMs) are widely used to calculate metabolic phenotypes. They rely on...
Genome-scale metabolic models (GEMs) can be used to evaluate genotype-phenotype relationships and th...
Cancer cells reprogram metabolism to support rapid proliferation and survival. Energy metabolism is ...
Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks ...
Genome-scale metabolic models (GEMs) computationally describe gene-protein-reaction associations for...
©2003 BioMed Central LtdOne of the challenges for ‘post-genomic’ biology is the integration of data ...
Background: Constraint-based models of Escherichia coli metabolic flux have played a key role in com...
The genome-scale model (GEM) of metabolism in the bacterium Escherichia coli K-12 has been in develo...
Genome-scale metabolic models have been utilized extensively in the study and engineering of the org...
Diverse datasets, including genomic, transcriptomic, proteomic, and metabolomic data are becoming re...
Genome-scale models of metabolism can illuminate the molecular basis of cell phenotypes. Since some ...
Abstract Background Synthetic biology and related techniques enable genome scale high-throughput inv...
Metabolic models are useful for a number of applications in the world of biology. If one understands...
Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks ...
Genome-scale metabolic modeling is an important tool in the study of metabolism by enhancing the col...
Genome‐scale metabolic models (GEMs) are widely used to calculate metabolic phenotypes. They rely on...
Genome-scale metabolic models (GEMs) can be used to evaluate genotype-phenotype relationships and th...
Cancer cells reprogram metabolism to support rapid proliferation and survival. Energy metabolism is ...
Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks ...
Genome-scale metabolic models (GEMs) computationally describe gene-protein-reaction associations for...
©2003 BioMed Central LtdOne of the challenges for ‘post-genomic’ biology is the integration of data ...