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“Metabolic networks remain the only class of biological network reconstructed reasonably comprehensively at the genome-scale in humans. Given that metabolic networks are ultimately based on directed chemical reactions that obey the laws of mass and energy balance, they can further serve the basis for calculations to predict reaction rates (metabolic flux). These fluxes can subsequently be used to compute productions and growth rates of metabolites. In flux balance analysis, the set of reactions is formulated as a stochiometric matrix, which enumerates the ratios of metabolite participation in each reaction. A set of physically possible reaction flux rates result by enforcing a steady-state mass balance (homeostasis) and additional constraints on reaction reversabilities and maximal conversion rates. From within the space of chemically feasible reaction flux combinations, the subset of biologically relevant reaction flux profiles can be solved by optimizing an objective function. The most commonly used objective function in microbes has been to maximize the production of biomass, which serves as a proxy for maximizing growth rate. Notably, while maximal growth may be an appropriate assumption for diseases such as cancer under certain conditions, the best cellular objective function to simulate many human tissues and cell types is unknown (and is likely condition-specific). Adjusting this objective function, which was developed based on microbial physiology, to better reflect human tissues is an area of active research.”