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Integrative analysis for finding genes and networks involved in diabetes and other complex diseases

Regine Bergholdt1, Zenia M Størling2, Kasper Lage2, E Olof Karlberg2, Páll Í Ólason2, Mogens Aalund3, Jørn Nerup14, Søren Brunak2, Christopher T Workman2 and Flemming Pociot14*

  • * Corresponding author: Flemming Pociot fpoc@steno.dk

  • † Equal contributors

Author Affiliations

1 Steno Diabetes Center, Niels Steensensvej 2, DK-2820 Gentofte, Denmark

2 Center for Biological Sequence Analysis, Technical University of Denmark, DK-2800 Lyngby, Denmark

3 Neurotech A/S, DK-2100 Copenhagen, Denmark

4 Institute for Clinical Science, University of Lund, SE-221 00 Lund, Sweden

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Genome Biology 2007, 8:R253  doi:10.1186/gb-2007-8-11-r253

Published: 28 November 2007

Abstract

We have developed an integrative analysis method combining genetic interactions, identified using type 1 diabetes genome scan data, and a high-confidence human protein interaction network. Resulting networks were ranked by the significance of the enrichment of proteins from interacting regions. We identified a number of new protein network modules and novel candidate genes/proteins for type 1 diabetes. We propose this type of integrative analysis as a general method for the elucidation of genes and networks involved in diabetes and other complex diseases.