Complex genetic disorders often involve multiple proteins interacting with each other, and pinpointing which of them are actually important for the disease is still challenging. Many computational approaches exploiting interaction network topology have been successfully applied to prioritize which individual genes may be involved in diseases, based on their proximity to known disease genes in the network.
In a paper published in PLoS One, Baldo Oliva, head of the Structural bioinformatics group at the GRIB (UPF–IMIM) and Emre Guney, have presented GUILD (Genes Underlying Inheritance Linked Disorders), a new genome-wide network-based prioritization framework. GUILD includes four novel algorithms that use protein-protein interaction data to predict gene-phenotype associations at genome-wide scale, and the authors have proved that they are comparable, or outperform, several known state-of-the-art similar approaches.
As a proof of principle, the authors have used GUILD to investigate top-ranking genes in Alzheimer’s disease (AD), diabetes and AIDS using disease-gene associations from various sources.
GUILD is freely available for download at http://sbi.imim.es/GUILD.php
Guney E, Oliva B. Exploiting Protein-Protein Interaction Networks for Genome-Wide Disease-Gene Prioritization. PLoS One. 2012;7(9):e43557