Abstract
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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Acknowledgements
M.M. was partially supported by the Army Research Laboratory, under Cooperative Agreement Number W911NF-09-2-0053. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the US Government. The US Government is authorized to reproduce and distribute reprints for government purposes notwithstanding any copyright notation here on. R.S. was supported by a research grant from the Israel Science Foundation (grant no. 385/06).
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Mongiovì, M., Sharan, R. (2013). Global Alignment of Protein–Protein Interaction Networks. In: Mamitsuka, H., DeLisi, C., Kanehisa, M. (eds) Data Mining for Systems Biology. Methods in Molecular Biology, vol 939. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-107-3_3
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DOI: https://doi.org/10.1007/978-1-62703-107-3_3
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