Adam M. Feist

TL;DR: The constraint-based reconstruction and analysis toolbox as discussed by the authors is a software package running in the Matlab environment, which allows for quantitative prediction of cellular behavior using a constraintbased approach and allows predictive computations of both steady-state and dynamic optimal growth behavior, the effects of gene deletions, comprehensive robustness analyses, sampling the range of possible cellular metabolic states and the determination of network modules.

TL;DR: An updated genome‐scale reconstruction of the metabolic network in Escherichia coli K‐12 MG1655 with increased scope and computational capability is presented, expected to broaden the spectrum of both basic biology and applied systems biology studies of E. coli metabolism.

TL;DR: The initial genome‐scale reconstruction of the metabolic network of Escherichia coli K‐12 MG1655 was assembled in 2000 and an update has now been built, named iJO1366, which accounts for 1366 genes, 2251 metabolic reactions, and 1136 unique metabolites.

TL;DR: The process that is currently used to achieve comprehensive network reconstructions is described and how these reconstructions are curated and validated is discussed to aid the growing number of researchers who are carrying out reconstructions for particular target organisms.

TL;DR: The field is expected to move forward and further broaden the scope and content of network reconstructions, develop new and novel in silico analysis tools, and expand in adaptation to uses of proximal and distal causation in biology.