We introduce a multi-scale kernel diffusion framework and apply it to a large collection of murine retroviral insertional mutagenesis data. The diffusion strength plays the role of scale parameter. As a result, in addition to detecting genes with frequent mutations in their genomic vicinity (red nodes in the interaction graph) we can also find genes that harbor frequent mutations in their interaction network context (white and pink nodes).