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A huge chasm exists at present between genomics and physiology, which must be closed if genomics is to fulfil its potential, already heavily embedded in the expectations of many pharmaceutical companies, to clarify bases for human disease and to identify effective targets for attack on pathogens. In spite of vast data sets, potent search and clustering algorithms, and great impact on biological research and biotechnology, genomics extends from databases only to certain aspects of protein biochemistry-physiology is still far in the distance, from this genomics side of the chasm.

In particular, if we can reasonably postulate the "goals" of a particular subset of cellular processes, then we can, by assuming that the cell controls its allocation of limited resources to this subsystem to maximally achieve these goals, predict the cell's actions. Taking a more specific example within the context of enzyme-catalysed metabolic pathways, by postulating the "goal" of a linear sequence of metabolic reactions (say, to operate at maximum rate) given a fixed allocation of resources to synthesize all of the enzymes in that pathway, one can solve the resulting optimization problem and "predict" the relative amounts of each enzyme that will be made by the cell.