Global Alignment of Protein–Protein Interaction Networks

Computer Science Department, University of California Santa Barbara, Santa Barbara, CA, USA.
Methods in molecular biology (Clifton, N.J.) (Impact Factor: 1.29). 01/2013; 939:21-34. DOI: 10.1007/978-1-62703-107-3_3
Source: PubMed


Sequence-based comparisons have been the workhorse of bioinformatics for the past four decades, furthering our understanding of gene function and evolution. Over the last decade, a plethora of technologies have matured for measuring Protein-protein interactions (PPIs) at large scale, yielding comprehensive PPI networks for over ten species. In this chapter, we review methods for harnessing PPI networks to improve the detection of orthologous proteins across species. In particular, we focus on pairwise global network alignment methods that aim to find a mapping between the networks of two species that maximizes the sequence and interaction similarities between matched nodes. We further suggest a novel evolutionary-based global alignment algorithm. We then compare the different methods on a yeast-fly-worm benchmark, discuss their performance differences, and conclude with open directions for future research.

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Available from: Misael Mongiovi
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