Current proteomic approaches include both broad discovery measurements and quantitative targeted analyses. In many cases, discovery measurements are initially used to identify potentially important proteins (e.g. candidate biomarkers) and then targeted studies are employed to quantify a limited number of selected proteins. Both approaches, however, suffer from limitations. Discovery measurements aim to sample the whole proteome but have lower sensitivity, accuracy, and quantitation precision than targeted approaches, whereas targeted measurements are significantly more sensitive but only sample a limited portion of the proteome. Herein, we describe a new approach that performs both discovery and targeted monitoring (DTM) in a single analysis by combining liquid chromatography, ion mobility spectrometry and mass spectrometry (LC-IMS-MS). In DTM, heavy labeled target peptides are spiked into tryptic digests and both the labeled and unlabeled peptides are detected using LC-IMS-MS instrumentation. Compared with the broad LC-MS discovery measurements, DTM yields greater peptide/protein coverage and detects lower abundance species. DTM also achieved detection limits similar to selected reaction monitoring (SRM) indicating its potential for combined high quality discovery and targeted analyses, which is a significant step toward the convergence of discovery and targeted approaches. The application of both discovery and targeted proteomics approaches is increasingly important across many areas of biological research, such as elucidating molecular mechanism of disease progression and increasing the utility of clinical applications to facilitate early detection and prognostic classification (1, 2). Currently discovery and targeted approaches are performed separately, limiting sample throughput and requiring more material for thorough analyses. In the prevalent discovery-based shotgun approach (3-6), proteins are digested into peptides, separated by liquid chromatography (LC) 1 , and detected by mass spectrometry (MS), where specific peptides are further selected (typically by abundance) for successive tandem MS/MS for identification. The resulting spectra are then mapped to peptide or protein sequences using highly-evolved database search algorithms with results normally obtained for thousands of unique proteins. However, the large numbers of coeluting peptides and use of MS/MS inevitably limit proteomic measurement effectiveness by at least one of three key metrics: throughput, sensitivity, and proteome coverage. To increase proteome coverage additional fractionation steps and/or extended LC separations are often applied. Although this is advantageous for increasing the comprehensiveness and sensitivity of measurements, the reduced throughput greatly restricts the ability to account for both measurement and biological variability. Additionally, these broad discovery measurements still suffer deficiencies