Additionally, we have compiled a list of proteomics publications that utilize ML, along with a list of ProteomeXchange datasets used by each of the publications (Supplementary Table ). Each of these ProteomeXchange datasets have been given a set of tags to indicate the nature of the usage in the publications (e.g., benchmarking, retention time, deep learning, etc.) as seen in Supplementary Table 31 . Furthermore, these tags have also been added to the respective PRIDE entries, which allows the tags to easily be searched, and for users to compile their ideal dataset, if ProteomicsML does not already contain one.