We describe an algorithm, IsoRank, for global alignment of two protein-protein interaction (PPI) networks. IsoRank aims to maximize the overall match between the two networks; in contrast, much of previous work has focused on the local alignment problem-identifying many possible alignments, each corresponding to a local region of similarity. IsoRank is guided by the intuition that a protein should be matched with a protein in the other network if and only if the neighbors of the two proteins can also be well matched. We encode this intuition as an eigenvalue problem, in a manner analogous to Google's PageRank method. We use IsoRank to compute the first known global alignment between the S. cerevisiae and D. melanogaster PPI networks. The common subgraph has 1420 edges and describes conserved functional components between the two species. Comparisons of our results with those of a well-known algorithm for local network alignment indicate that the globally optimized alignment resolves ambiguity introduced by multiple local alignments. Finally, we interpret the results of global alignment to identify functional orthologs between yeast and fly; our functional ortholog prediction method is much simpler than a recently proposed approach and yet provides results that are more comprehensive. Corresponding Author. Also with the Department of Mathematics, MIT interaction between the proteins. Computational analyses of these networks has already yielded valuable insights: the scale-free character of these networks and the disproportionate importance of "hub" proteins [30] ; the combination of these networks with gene expression data to discern some of the dynamic character of the cell [8]; the use of PPI networks for inferring biological function [20] , etc. As more PPI data becomes available, comparative analysis of PPI networks (across species) is proving to be a valuable tool. Such analysis is similar in spirit to traditional sequence-based comparative genomic analyses; it also promises commensurate insights. Such an analysis can identify conserved functional components across species [15] . As a phylogenetic tool, it offers a function-oriented perspective that complements traditional sequence-based methods. It also facilitates annotation transfer between species. Indeed, Bandyopadhyay et al. [3] have demonstrated that the use of PPI networks in computing orthologs produces orthology mappings that better conserve protein function across species. In this paper, we explore a new approach to comparative analysis of PPI networks. Specifically, we consider the problem of finding the optimal global alignment between two PPI networks, aiming to find a correspondence between nodes and edges of the input networks that maximizes the overall match between the two networks. For this problem, we propose a novel pairwise global alignment algorithm, IsoRank.
One of the key studies on pairwise global network alignment is IsoRank REF , which is based on the conjecture that two nodes should be matched if their respective neighbors can also be matched.
Pairwise global alignment of protein interaction networks by matching neighborhood topology
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Mathematics Computer Science