Computational modeling, particularly constraint-based modeling of bacterial metabolism from a genome-scale network exhibits promising attributes when looking at genotype-to-metabolicphenotype relations or microbe–microbe and host–microbe metabolic interactions. This approach requires the conversion of a human or microbial genome sequence into a metabolic reconstruction and further, the transformation into a condition-specific model. Thereby, a biochemical reaction list is converted into a computable, stoichiometric matrix format on the basis of existing experimental data [151]. Next, as all cellular networks operate within boundaries of physical and chemical constraints, mathematical constraints are also applied to the model. Finally, via flux balance analysis, a computed steady-state flux space contains all feasible steadystate flux distributions for the biochemical network and thereby predicts the metabolic phenotype