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 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.