Reconstruction And Simulation Of The Metabolic Network Of Human Erythrocyte

In the post-genome era, bioinformatics methods play an important role in unraveling the complex mechanisms inside biological systems. Conventional molecular biological approaches, though very useful in studying the functions of single gene or protein, could not meet the demands of understanding the dynamic interactions in the whole biological systems, such as a cell, an organ, etc. With the development of high throughput technology, tons of experimental data accumulate, made it possible the growth of"systems biology". Systems biology tries to understand the biological systems at the systematic level. In this field, modeling and simulation of biochemical networks is one of the most important steps. Current research could be divided into two categories: structural analysis of the network based on graph theory, dynamic system analysis of the network based on differential equations.In this thesis, we present mainly two works in studying the metabolic network of human red blood cell. One is structural analysis of the network using Petri Net theory and tools. Comparing with previous achievements, we integrated the total three pathways into a model for the first time in the world and successfully built the modular Petri Net model. The other is dynamic analysis of the network using the E-Cell simulation system of the red blood cell. We quantitatively investigate the network response to enzymatic diseases. Expected results were gained. Moreover, analysis of surprising results showed kinetic-unfavored but thermodynamics-favored phenomena happened. The robustness of the network was revealed. Careful biological explanation was provided. The conclusion was that when the deficiency proportion of pyruvate kinase was less than 15%, the cell could resist the enzymatic disease; otherwise, the metabolism of the cell would greatly decrease, ultimately the cell would die.