Genome-Scale Models of Metabolic and Regulatory Networks - Systems Biology: Networks, Models, and Applications - page 255

in many cell types have accumulated to allow reconstruction of
these networks in a stoichiometric formalism [117,118]. These recon-
structions can then be subjected to the same constraint-based analysis
methods used to study metabolic networks, to investigate network-
level characteristics such as cross-talk or redundancy. The basic processes
involved in protein synthesis, transcription and translation, are also
amenable to genome-scale constraint-based modeling [119,120].
Nonmetabolic processes such as signaling or transcription have tradi-
tionally been modeled on a relatively small scale using either stochastic
or deterministic kinetic approaches [121]. Large-scale constraint-based
models can complement these models by providing a more complete
picture of the interconnectivity between different modules in, for
example, signaling pathways.
One of the future challenges will be integration of the individual
models of these different cellular processes to allow systematic analysis
of whole cell function. Achieving this integration will require further
developments in constraint-based analysis, to represent solution spaces
for protein and metabolite concentrations, in addition to metabolic
fluxes [122,123]. Extension of genome-scale constraint-based models to
additional types of cellular processes, and continued development of
in silico methods, will enable more accurate prediction of cellular
behavior. Combination of in silico analysis of genome-scale models
and experimentation will also allow systematic study of the underly-
ing operational principles of biochemical networks.
ACKNOWLEDGMENTS
We thank Nathan Price, Markus Covert, Jennifer Reed, and Stephen Fong for
assistance in preparing figures. We acknowledge the support of the National
Science Foundation and the National Institutes of Health.
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