Scientists from UCLA and the University of Toronto have developed moPepGen, an innovative algorithm that enhances the detection of complex protein variants stemming from diverse genetic alterations including alternative splicing, gene fusions, and RNA editing. Published in Nature Biotechnology, moPepGen leverages graph-based computational strategies to overcome limitations of traditional proteomic tools, facilitating the discovery of neoantigens critical for personalized cancer therapies and broadening understanding of disease mechanisms at the protein expression level.