Lawrence Berkeley National Laboratory

Proteomics is, by definition, comprehensive and large-scale, seeking to unravel ome-level protein features with phenotypic information on an entire system, an organ, cells, or organisms. This scope consistently involves and extends beyond single experiments. Multitudinous resources now exist to assist in making the results of proteomics experiments more findable, accessible, interoperable, and reusable (FAIR), yet many tools are awaiting to be adopted by our community. Here we highlight strategies for expanding the impact of proteomics data beyond single studies. We show how linking specific terminologies, identifiers, and text (words) can unify individual data points across a wide spectrum of studies and, more importantly, how this approach may potentially reveal novel relationships. In this effort, we explain how data sets and methods can be rendered more linkable and how this maximizes their value. We also include a discussion on how data linking strategies benefit stakeholders across the proteomics community and beyond.