Modeling And Analysis Of Multi-scale Complex Biological Network

As a new emerging cross discipline with physics, systems, computer science and life science, network biology is aim to systematically catalogue, analyze, regulate and optimize networks embedded in biological systems. In biology and ecology, there is a clear need to understand how these components (from DNA, metabolite, cell, specie to even ecosystem) and the interactions between them determine the function of related enormously complex systems. Rapid advances in network biology indicate that biological networks are governed by some universal laws and offer a new conceptual framework that could potential revolutionize our view of biology and ecology in the twenty-first century.Mathematical models and related analyzing methods and tools as formal representation are central for handling the associated complex biological networks. In the present work, we attempt to address three major challenges in network biology and ecology research:a) finding the more effective methods for evaluating robustness in biological networks; b) exploring the properties of ecological networks in newly emerged coupled human and natural systems; and c) constructing the mathematical platform for sharing concepts, models and methods between biology and ecology.The main contents of this thesis are as follows:1) We develop a novel pathway knockout algorithm to improve quantitative measure of redundancy in metabolic networks grounded on elementary mode analysis. We demonstrated with four example systems that our algorithm overcomes limits of previous measures, and provides additional information about redundancy in the situation of targeted attacks.2) We extend the mean-field analysis to the context of pathway analysis, and mathematically prove that multiple-enzymes knockout does not always yield more information than single-enzyme knockout for evaluating redundancy.3) The metabolic networks of amino acid anabolism in Escherichia coli and human hepatocytes, and the central metabolism in human erythrocytes have been study with pathway knockout algorithm. The results provide new insight for these real world networks.4) We use network environ analysis to investigate and compare indirect effects of nitrogen cycling networks in 22 natural and five urban systems. Our works focus on:a) explore weak indirect effects of nitrogen cycling networks in urban areas, and b) test the hypothesis in which way biogeochemistry in urban areas is different and more complex than it in natural ecosystems. In addition, we also initially discuss the regulation strategy for urban nitrogen cycling networks.5) In order to provide new models for new coupled human and natural systems, we explore the rigorous similarities between biogeochemical and biochemical cycles. Based on it, we present a systems biology framework for urban nitrogen metabolic network reconstruction, and import constraint-based analyzing tools from network biology to study the reconstructed networks.6) New tools are necessary to model and analyze the highly complex nitrogen cycles emerging from coupled human and natural systems. We developed new software to provide three functions:a) rigorous reconstruction of quasi-empirical models, b) computer-aided interface for data collection and automatic sensitivity analysis, and c) automatic generation, visualization and network environ analysis of nitrogen cycling networks.