Functional cartography of complex metabolic networks
Functional cartography of complex metabolic networks
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DOI：
10.1038/nature03288
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发表时间：
2005-02-24
期刊：
影响因子：
64.8
通讯作者：
Amaral, LAN
中科院分区：
文献类型：
--
作者：
Guimerà, R;Amaral, LAN
高通量技术正在导致生物数据库规模的爆炸性增长，并为我们对生命和疾病的理解带来革命性的机会。然而，对这些数据的解释仍然是一个重大的科学挑战。在这里，我们提出了一种方法，使我们能够提取和显示复杂网络中包含的信息（1-3）。具体来说，我们证明了我们可以在复杂网络中找到功能模块（4，5），并根据它们的模块内和模块间连接模式将节点分类为通用角色。因此，该方法产生了复杂网络的“制图表示”。代谢网络（6-8）是最具挑战性的生物网络之一，也是最有可能立即应用的网络（9）。我们使用我们的方法来分析来自三个不同超级王国的十二种生物的代谢网络。我们发现，通常情况下，80%的节点只连接到各自模块内的其他节点，并且具有不同角色的节点受到不同进化约束和压力的影响。值得注意的是，我们发现只参与少数反应但连接不同模块的代谢物比其链接主要在单个模块内的枢纽更保守。
High-throughput techniques are leading to an explosive growth in the size of biological databases and creating the opportunity to revolutionize our understanding of life and disease. Interpretation of these data remains, however, a major scientific challenge. Here, we propose a methodology that enables us to extract and display information contained in complex networks(1-3). Specifically, we demonstrate that we can find functional modules(4,5) in complex networks, and classify nodes into universal roles according to their pattern of intra- and inter-module connections. The method thus yields a 'cartographic representation' of complex networks. Metabolic networks(6-8) are among the most challenging biological networks and, arguably, the ones with most potential for immediate applicability(9). We use our method to analyse the metabolic networks of twelve organisms from three different superkingdoms. We find that, typically, 80% of the nodes are only connected to other nodes within their respective modules, and that nodes with different roles are affected by different evolutionary constraints and pressures. Remarkably, we find that metabolites that participate in only a few reactions but that connect different modules are more conserved than hubs whose links are mostly within a single module.