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Network translation has recently been used to establish steady stateproperties of mass action systems by corresponding the given system to ageneralized one which is either dynamically or steady state equivalent. In thiswork we further use network translation to identify network structures whichgive rise to the well-studied property of absolute concentration robustness inthe corresponding mass action systems. In addition to establishing the capacityfor absolute concentration robustness, we show that network translation canoften provide a method for deriving the steady state value of the robustspecies. We furthermore present a MILP algorithm for the identification oftranslated chemical reaction networks that improves on previous approaches,allowing for easier application of the theory.

Network translation and steady state properties of chemical reaction systems