The ultimate result of a proteomics study is a list of proteins found to be present (or differentially present) at various cell physiological conditions. Normally the results are presented in a publication in one or several tables. The bulk of his type of information remains dispersed in hundreds of proteomics related publications. We have developed a web mining tool which allows collecting this information by searching through full text papers and automatically selecting tables, which report a list of protein identifiers. By searching through major proteomics journals, we have collected approximately 800 independent studies published recently, which reported about 1000 different protein lists. Based on this data, we developed a computational tool PLIPS (Protein Lists Identified in Proteomics Studies). PLIPS accepts as input a list of protein/gene identifiers. Using statistical analyses PLIPS identifies recently published proteomics studies, which report protein lists that significantly intersects with a query list.