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Nat Rev Genet. 2017 Sep;18(9):551-562. doi: 10.1038/nrg.2017.38. Epub 2017 Jun 12.

Network propagation: a universal amplifier of genetic associations.

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Department of Computer Science, Tufts University, Medford, Massachusetts 02155, USA.
University of California San Diego, La Jolla 92093, California, USA.
Department of Computer Science, Princeton University, Princeton, New Jersey 08540, USA.
Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel.


Biological networks are powerful resources for the discovery of genes and genetic modules that drive disease. Fundamental to network analysis is the concept that genes underlying the same phenotype tend to interact; this principle can be used to combine and to amplify signals from individual genes. Recently, numerous bioinformatic techniques have been proposed for genetic analysis using networks, based on random walks, information diffusion and electrical resistance. These approaches have been applied successfully to identify disease genes, genetic modules and drug targets. In fact, all these approaches are variations of a unifying mathematical machinery - network propagation - suggesting that it is a powerful data transformation method of broad utility in genetic research.

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