The broad application of proteomics in different biological and medical fields, as well as the diffusion of high-throughput platforms, leads to increasing volumes of available proteomics data. Computational proteomics is the data science concerned with the identification and quantification of proteins from numerous data sources and the biological interpretation of their concentration changes, posttranslational modifications, interactions, and subcellular localizations. Computational proteomics is a highly multidisciplinary endeavor attracting scientists from many fields and incorporates other disciplines like statistics, machine learning, efficient scientific programming, and network and time series analysis.