New directions for diffusion-based network prediction of protein function: incorporating pathways with confidence

Bioinformatics (Impact Factor: 4.62). 06/2014; 30(12):i219-i227. DOI: 10.1093/bioinformatics/btu263
Source: PubMed

ABSTRACT It has long been hypothesized that incorporating models of network noise as well as edge directions and known pathway information into the representation of protein-protein interaction (PPI) networks might improve their utility for functional inference. However, a simple way to do this has not been obvious. We find that diffusion state distance (DSD), our recent diffusion-based metric for measuring dissimilarity in PPI networks, has natural extensions that incorporate confidence, directions and can even express coherent pathways by calculating DSD on an augmented graph.

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Available from: Benjamin J. Hescott, Jan 15, 2015
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