Mutation is the hallmark of cancer. Computational deconvolution approaches have revealed the mutational signatures of many different dysregulated processes in cancer. From August 2013 to now, five versions of mutational signatures have been published. The very first analysis only identified 20 distinct mutational signature, but the latest version reports 94 signatures. Here we report a computational approach based on the popular network analysis technique, link prediction, to improve the identification of mutational signatures.
