Topological anaylysis and prediction of aging genes in Mus musculus

An important task of aging research is to find genes that regulate lifespan. Wet-lab identification of aging genes is a tedious and labor-intensive activity. Developing an algorithm to predict aging genes for guiding wet-lab experiment should be greatly helpful. In this paper, we systematically analyzed topological features of proteins encoded by Mus musculus aging genes versus those encoded by non-aging genes in protein-protein interaction (PPI) network and found that aging genes are characterized by several network topological features such as higher in degrees. Based on these features, an algorithm was developed to detect aging genes genome wide. With a score higher than 0.8, describing possibility of involvement in aging, 110 novel aging genes were predicted. Evidences supporting our prediction can be found.