摘要：The multi-scale modelling approach is a powerful mathematical technique for simulating and analyzing complex biological systems such as the human body. This tool can help study the interactions of the various networks in a living organism, from the cellular level up to the population scale, in one framework. In this paper, a generic mathematical model is developed that describes human metabolism with 237 serum metabolites integrated with a chosen set of human metabolic networks. A new computational approach is presented for solving the resulting dynamic problem using parsimonious flux balance analysis (pFBA). To illustrate the performance of the proposed approach, the human hepatocyte genome scale model is selected for the metabolic network to be included. The simulation results show that the proposed approach has promise with respect to both computational efficiency and convergence. To demonstrate the potential application of the developed model, prediction of amino acid biomarkers for a set of inborn errors of metabolism (IEM) is considered as an example. All the simulations are performed using MATLAB and the COBRA toolbox. This framework has the potential to simulate various human metabolic disorders to help with the diagnosis of associated human diseases and to suggest novel treatment strategies. In addition, it opens the door to new opportunities for personalized medicine.
关键词：Multi-scale modellingwhole-body modelmetabolic networkflux balance analysispersonalized medicine
