Graph spectral analysis of protein interaction network evolution.

Journal of the Royal Society, Interface
Thomas Thorne, Michael P H Stumpf

Abstract

We present an analysis of protein interaction network data via the comparison of models of network evolution to the observed data. We take a bayesian approach and perform posterior density estimation using an approximate bayesian computation with sequential Monte Carlo method. Our approach allows us to perform model selection over a selection of potential network growth models. The methodology we apply uses a distance defined in terms of graph spectra which captures the network data more naturally than previously used summary statistics such as the degree distribution. Furthermore, we include the effects of sampling into the analysis, to properly correct for the incompleteness of existing datasets, and have analysed the performance of our method under various degrees of sampling. We consider a number of models focusing not only on the biologically relevant class of duplication models, but also including models of scale-free network growth that have previously been claimed to describe such data. We find a preference for a duplication-divergence with linear preferential attachment model in the majority of the interaction datasets considered. We also illustrate how our method can be used to perform multi-model inference of network...Continue Reading

References

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May 10, 2006·Proceedings of the National Academy of Sciences of the United States of America·Carsten WiufMichael P H Stumpf
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Citations

Apr 13, 2013·Current Opinion in Biotechnology·Paul KirkMichael P H Stumpf
Apr 2, 2014·Scientific Reports·Ömer Nebil YaveroğluNataša Pržulj
Mar 27, 2015·Bioinformatics·Ömer Nebil YaveroğluNataša Pržulj
Oct 17, 2017·Bioinformatics·Andrew ElliottFelix Reed-Tsochas
Jul 22, 2014·Clinical and Experimental Allergy : Journal of the British Society for Allergy and Clinical Immunology·J R PerkinsJ A Cornejo-Garcia
Aug 9, 2020·Journal of Complex Networks·Sixing ChenJukka-Pekka Onnela
Oct 22, 2020·Journal of the Royal Society, Interface·Michael P H Stumpf

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Software Mentioned

CULAtools
GPGPU
CULAtools GPU linear algebra
LAPACK

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