ABSTRACT
This chapter overviews different constraint-based approaches, that go beyond the linear biomass objective, and attempts to predict the state of the cell in many other conditions. It discusses techniques to integrate omic data, particularly transcriptomic data, to explore the relationship between metabolism and regulation. Church and co-workers proposed Minimisation of Metabolic Adjustment (MoMA) in 2002. The MoMA formulation is directly useful to fit experimentally measured fluxes; these are typically obtained through 13C labelling. Regulatory On-Off Minimisation (ROOM) is another constraint-based analysis technique, in the flavour of MoMA. While methods such as MoMA and ROOM are nowhere as widely used as Flux Balance Analysis, they present useful methodologies that provide a different perspective on studying/predicting the flux state of a cell. OptKnock is one of the classic strain design methods, which proposed a bi-level optimisation problem that maximises a given bio-engineering design objective, concurrently with the maximisation of biomass.
