Huss M, Holme P
School of Computer Science and Communication, Royal Institute of Technology, Stockholm 100 44, Sweden.
IET Syst Biol. 2007 Sep;1(5):280-5. doi: 10.1049/iet-syb:20060077.
The large-scale shape and function of metabolic networks are intriguing topics of systems biology. Such networks are on one hand commonly regarded as modular (i.e. built by a number of relatively independent subsystems), but on the other hand they are robust in a way not necessarily expected of a purely modular system. To address this question, we carefully discuss the partition of metabolic networks into subnetworks. The practice of preprocessing such networks by removing the most abundant substances, 'currency metabolites', is formalized into a network-based algorithm. We study partitions for metabolic networks of many organisms and find cores of currency metabolites and modular peripheries of what we call 'commodity metabolites'. The networks are found to be more modular than random networks but far from perfectly divisible into modules. We argue that cross-modular edges are the key for the robustness of metabolism.
代谢网络的大规模形态和功能是系统生物学中引人入胜的课题。一方面，这类网络通常被视为模块化的（即由一些相对独立的子系统构建而成），但另一方面，它们具有一种未必是纯粹模块化系统所具有的稳健性。为了解决这个问题，我们仔细讨论了将代谢网络划分为子网络的方法。通过去除最丰富的物质“通用代谢物”对这类网络进行预处理的做法被形式化为一种基于网络的算法。我们研究了许多生物体代谢网络的划分，发现了通用代谢物的核心以及我们所称的“商品代谢物”的模块化外围。研究发现这些网络比随机网络更具模块化，但远未达到能完美地划分为模块的程度。我们认为跨模块的边是代谢稳健性的关键。
