Discovering disease-associated genes in weighted protein–protein interaction networks

Although there have been many network-based attempts to discover disease-associated genes, most of them have not taken edge weight – which quantifies their relative strength – into consideration. We use connection weights in a protein–protein interaction (PPI) network to locate disease-related genes. We analyze the topological properties of both weighted and unweighted PPI networks and design an improved random forest classifier to distinguish disease genes from non-disease genes. We use a cross-validation test to confirm that weighted networks are better able to discover disease-associated genes than unweighted networks, which indicates that including link weight in the analysis of network properties provides a better model of complex genotype–phenotype associations.