In the absence of direct measurements, a conceptually straightforward way to obtain an estimate of intracellular fluxes is probabilistic sampling of the feasible space using a Bayesian framework and Markov Chain Monte Carlo 51 that integrates all available measurements and biophysical constraints. For example, the feasible space defined by CORE measurements and proliferation rates can be further constrained using transcriptomics by requiring fluxes to align with reaction activity scores . Moreover, fluxes can be required to satisfy energy balance , thereby eliminating unrealistic loops that satisfy mass balance but violate the second law of thermodynamics.