Department of Computer Science, University of California, Irvine, CA 92697-3435, USA.
J R Soc Interface. 2010 Sep 6;7(50):1341-54. doi: 10.1098/rsif.2010.0063. Epub 2010 Mar 17.
Sequence comparison and alignment has had an enormous impact on our understanding of evolution, biology and disease. Comparison and alignment of biological networks will probably have a similar impact. Existing network alignments use information external to the networks, such as sequence, because no good algorithm for purely topological alignment has yet been devised. In this paper, we present a novel algorithm based solely on network topology, that can be used to align any two networks. We apply it to biological networks to produce by far the most complete topological alignments of biological networks to date. We demonstrate that both species phylogeny and detailed biological function of individual proteins can be extracted from our alignments. Topology-based alignments have the potential to provide a completely new, independent source of phylogenetic information. Our alignment of the protein-protein interaction networks of two very different species-yeast and human-indicate that even distant species share a surprising amount of network topology, suggesting broad similarities in internal cellular wiring across all life on Earth.
序列比对和比对分析对我们理解进化、生物学和疾病产生了巨大的影响。生物网络的比对和比对分析可能也会产生类似的影响。现有的网络比对分析使用网络外部的信息,如序列,因为还没有设计出用于纯拓扑比对的好算法。在本文中,我们提出了一种仅基于网络拓扑的新算法,可用于对齐任意两个网络。我们将其应用于生物网络,以生成迄今为止最完整的生物网络拓扑比对。我们证明可以从我们的比对中提取物种系统发育和单个蛋白质的详细生物学功能。基于拓扑的比对有可能提供全新的、独立的系统发育信息来源。我们对两种非常不同的物种(酵母和人类)的蛋白质-蛋白质相互作用网络进行的比对表明,即使是亲缘关系较远的物种也共享大量的网络拓扑结构,这表明地球上所有生命的内部细胞布线都有广泛的相似之处。