A genome-scale model of Arabidopsis metabolism

构成生物有机体细胞的分子并不是孤立地发挥作用，而是通过与其他分子相互作用来发挥作用。因此，细胞由相互作用的分子组成的复杂网络组成。由于单个分子的行为不仅受其自身属性的影响，而且还受相互作用的分子的影响，因此网络显示出新的属性--也就是说，不能简单地根据其组件的单独属性来预测整个网络的行为。掌握网络行为的一种方法是构建数学模型，允许计算网络参数。这项提议旨在建立一个数学模型，为模式植物拟南芥的代谢网络提供洞察力。新陈代谢是所有生物网络中描述得最好、研究最多的一种，但我们对新陈代谢作为一个整体的行为的了解仍然相当有限。数学模型不仅将为控制植物代谢网络的基本方面提供新的见解，而且还将是一个有用的工具，使人们能够预测操纵代谢中间体流动的最佳方式。这种代谢工程是培育新品种作物的努力的重要组成部分，这些新品种的作物能够更好地应对不断变化的全球气候和提高产量的要求带来的挑战。

The molecules that make up the cells of biological organisms do not function in isolation but do so by interacting with other molecules. Cells thus consist of a complex network of interacting molecules. Because the behaviour of an individual molecule is influenced not only by its own properties but also by those of interacting molecules, networks display emergent properties - that is the behaviour of the network as a whole cannot be simply predicted from the properties of its components in isolation. One way of getting to grips with network behaviour is to construct mathematical models that allow network parameters to be computed. This proposal aims to generate a mathematical model that will provide insight into the metabolic network of the model plant species, Arabidopsis thaliana. Metabolism is one of the best described and most studied of all biological networks and yet our understanding of the behaviour of metabolism as a whole remains rather limited. A mathematical model will not only provide new insight into fundamental aspects of control of the plant metabolic network, but it will also be a useful tool to allow predictions to be made about the best way to manipulate the flow of metabolic intermediates. Such metabolic engineering is an important part of attempts to generate new varieties of crop plants that are better equipped to deal with challenges imposed by a changing global climate and the requirements for increased yield.