Abstract
AbstractSequence comparison and alignment has had an enormous impact on our understanding of evolution, biology, and disease. Comparison and alignment of biological networks will likely 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 with each other, suggesting broad similarities in internal cellular wiring across all life on Earth.
Highlights
Introduction and MotivationAdvances in high throughput experimental methods have yielded large amounts of biological network data, such as protein-protein interaction (PPI) networks
We focus on topology instead of protein sequence because we aim to discover biological knowledge that is encoded in the PPI network topology
Entirely different sequences can produce identical structures.[32, 35]. In cases where such proteins are expected to share a common function, sequence-based function prediction would fail, where network topology-based one would not. We show that both sequence and topology have similar predictive power with respect to Gene Ontology (GO) terms[36] (Supplementary Figure 1), demonstrating that network topology can provide as much functional information as protein sequences
Summary
Advances in high throughput experimental methods have yielded large amounts of biological network data, such as protein-protein interaction (PPI) networks. As more biological network data is becoming available, comparative analyses of these networks across species are proving to be valuable, since such systems biology types of comparisons may lead to transfer of knowledge between species as well as to exciting discoveries in evolutionary biology. In the biological context, comparing networks of different organisms in a meaningful manner is arguably one of the most important problems in evolutionary and systems biology.[13] Exactly analogous to sequence alignments between genomes, alignments of biological networks can be useful because we may know a lot about some of the nodes in one network and almost nothing about topologically similar nodes in the other network; specialized knowledge about one may tell us something new about the other. Given a group of such biological networks, the matrix of pairwise global network similarities can be used to infer phylogenetic relationships
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