Title: Protein interaction networks associated with cardiovascular disease and cancer: exploring the effect of bias on shared network properties

Authors: Richard J.B. Dobson; Patricia B. Munroe; Mark J. Caulfield; Mansoor A.S. Saqi

Addresses: Genome Centre, The William Harvey Research Institute and Institute of Cell and Molecular Science Bart's and the London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK; King's College London, Institute of Psychiatry, King's Health Partners Centre for Neurodegeneration Research, London, UK ' Genome Centre, The William Harvey Research Institute and Institute of Cell and Molecular Science Bart's and the London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK ' Genome Centre, The William Harvey Research Institute and Institute of Cell and Molecular Science Bart's and the London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK ' Genome Centre, The William Harvey Research Institute and Institute of Cell and Molecular Science Bart's and the London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK; Department of Biomathematics and Bioinformatics, Rothamsted Research, Herpenden, Herts, UK

Abstract: The human network of Protein-Protein Interactions (PPIs) (interactome) provides information on biological systems that can be used to aid prediction of protein function and disease association. As some classes of protein may be the focus of much study, data sets may contain bias, which may affect the results of network analyses. Implicated cancer proteins and proteins including significant known mediators of cardiovascular disease (CVD) display a tendency to play a central role in a previously constructed interactome. However, removing possible bias in the interactome by only considering interactions obtained from non-targeted approaches affects the significance of the findings.

Keywords: PPI; protein-protein interaction; protein interaction networks; network analysis; cardiovascular disease; cancer proteins; disease networks; bias effect; shared network properties; interactome.

DOI: 10.1504/IJDMB.2014.062150

International Journal of Data Mining and Bioinformatics, 2014 Vol.9 No.4, pp.339 - 357

Received: 07 May 2011
Accepted: 29 Dec 2011
Published online: 21 Oct 2014 *

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