Model reduction of biochemical networks

Biochemical networks are not only complex but also extremely large. The construction and analysis for the mathematical model is thus relatively difficult. In practice, it is usually desirable to further simplify the structure of biological system models for the sake of reducing computation burden or simplification of the task of analysis. By introducing the technique of singular value decomposition it is possible to identify the major flux rate and hence deduce the corresponding signal transduction path. In this paper, a model reduction technique deduced from control theory is proposed to reduce that kind of systems.