Constraint-based modeling techniques have become a standard tool for the in silico
analysis of metabolic networks. To further improve their accuracy, recent methodological …

Constraint-based methods provide powerful computational techniques to allow
understanding and prediction of cellular behavior. These methods rely on physiochemical …

High-throughput data generation and genome-scale stoichiometric models have greatly
facilitated the comprehensive study of metabolic networks. The computation of all feasible …

Introducing biosynthetic pathways into an organism is both reliant on and challenged by
endogenous biochemistry. Here we compared the expansion potential of the metabolic …

Constraint-based modeling is an approach for quantitative prediction of net reaction flux in
genome-scale biochemical networks. In vivo, the second law of thermodynamics requires …

Background The availability of genome sequences for many organisms enabled the
reconstruction of several genome-scale metabolic network models. Currently, significant …

The integration of various types of genomic data into predictive models of biological
networks is one of the main challenges currently faced by computational biology. Constraint …

Genome-scale network reconstructions are useful tools for understanding cellular
metabolism, and comparisons of such reconstructions can provide insight into metabolic …

Genome-scale metabolic network models can be reconstructed for well-characterized
organisms using genomic annotation and literature information. However, there are many …

Genome-scale metabolic models of organisms can be reconstructed using annotated
genome sequence information, well-curated databases, and primary research literature. The …