Our findings clearly suggest a distinction between body representations in FBA and EBA: Functional connectivity in our study was more consistent between FBA and motor areas than between EBA and motor areas.
The maximization of cell growth rate usually served as the objective function in FBA.
In FBA, the RNC allocates resources on the backhaul before MT transmission based on a partial CSI.
The problem in FBA and its extension to genome-scale is the difficulty for the dynamic analysis as compared to kinetic modeling approach.
The constraints used in FBA include the balance of intracellular metabolites (Eq. 2), the reversibility and the demarcation line of reactions, as well as the extracellular metabolite exchange rates (Eq. 3).
In particular, while OBA has as input the actual rates achieved on the wireless link, in FBA we consider the statistics of the rate on the wireless link, and we aim at maximizing the expected weighted throughput.
In the comparison between FBA and OBA, we conclude that the perfect channel knowledge exploited in FBA allows for a better usage of the backhaul, with a reduction to a half or one-third of the occupancy required by OBA.
Amazon has been at this for 10+ years (FBA was launched in 2006), and I think the investment in FBA is a substantial part of the reason for their failure to make a profit (or, really, their choice to not make a profit) for the large part of the last decade.
Rather than optimizing the objective for one cell or metabolic network, as occurs in FBA, we seek to optimize the response of one cell in a population while minimizing the response of other cells in the population.
The problem is usually severely underdetermined in FBA.
In FBA, fluxes are constrained by steady-state mass balances, enzyme capacities and reaction directionality.
