Projection-Based Model Order Reduction for Biochemical Systems

Abstract

Biochemical systems represent a process that involves different biological species linked by a network of chemical reactions. This particular paper focuses on modeling and analysis (computer simulation) of biochemical systems. The problem with mathematical models is, their complexity. Numerical simulation of such complex models is computationally expensive. Model order reduction can be utilized to tackle this issue of complexity by eliminating those parts of a reaction network that do not contribute up to the mark in our parameters of interest. In this paper, we are using an important projection based model reduction technique, called IRKA, for model reduction of biochemical systems. The results of IRKA are compared with lumping, which is a common reduction technique for chemical reactions. It is observed that the approximation error through IRKA is much less as compared to the lumping technique.