Flux balance analysis-based ranking for model order reduction of biochemical networks

Abstract

Abstract This paper presents a parameter free approach to identify the importance of reactions (and involved species) in biochemical reaction networks for the purpose of model order reduction. The new methodology is based on the structure of the network assuming that at steady state the flux distribution is preserved. Our method employs Flux Balance Analysis (FBA) to calculate these flux distributions. The ranking is based on the comparison of the FBA results of the original and reduced networks. The main purpose of this identification step is to guide the selection of species that could be deleted by model order reduction methods. Our ranking method is illustrated in a model for Glycolysis, where model reduction is performed via the Kron reduction method considering the elimination of the less sensitive species proposed by the ranking method. The reduced model shows that the global dynamics could be accurately reproduced with a smaller number of species.