Gene reachability using page ranking on gene Co-expression networks

We modify the Google Page-Rank algorithm, which is primarily used for ranking web pages, to analyze the gene reachability in complex gene co-expression networks. Our modification is based on the average connections per gene. We propose a new method to compute the metric of average connections per gene, inspired by the Page-Rank algorithm. We calculate this average as eight for human genome data and three to seven for yeast genome data. Our algorithm provides clustering of genes. The proposed analogy between web pages and genes may offer a new way to interpret gene networks.