Numerous studies have generated large-scale datasets on human protein-protein interactions. However, many interactions remain undiscovered, particularly low-affinity, conditional, and cell type-specific interactions, which are disproportionately underrepresented. Most of these missing interactions are likely mediated by short linear motifs (SLiMs). Over the past decade, we have developed dedicated experimental methods for large-scale screening of SLiM-based interactions, along with tools and guidelines for data processing. Our optimized proteomic peptide-phage display (ProP-PD) library tiles the disordered regions of the human proteome, enabling the screening of approximately one million overlapping peptides in a single assay. To date, we have released data on over 2,000 SLiM-based interactions, and we have a major new dataset currently in preparation. The amino acid resolution of our interaction data allows for the prediction of functionally important disease mutations and phosphorylation events. Recently, we developed a tailored phage peptidome to pinpoint the effects of disease-associated mutations. By screening a collection of 80 bait proteins, we identified nearly 370 mutation-modulated interactions, with mutations either weakening, enhancing, or creating novel binding interfaces. Finally, we are also charting how viruses mimic and hijack SLiM-mediated interactions. Collectively, our findings provide novel insights into SLiM-mediated interactions that contribute to shaping the cellular interactome and reveal how disease-associated mutations may perturb or rewire the interactome.​ ​