Following the paradigm of the human genome project, much of current systems biology research entails characterizing, quantifying, and cataloging the biomolecular inventory of a sample at specific dimensions of space (e.g., cellular, tissue, or organism levels) and time (e.g., point in the life cycle, healthy vs. diseased state). These largely hypothesis-independent data are then integrated with the development of bioinformatic algorithms to derive an understanding of how different molecular networks interact and function, which subsequently provide a framework for performing hypothesis-driven studies [1]. This reductionist approach (i.e., measuring gene and protein expression levels, evaluating protein post-translational modifications, metabolite levels, etc.) is necessary to begin parameterizing the extraordinarily complex molecular interaction networks that regulate, control, and perturb biochemical processes, rather than directly analyzing the biological entity in its entirety. Quantitation of gene transcription is dominated by the use of gene arrays, while protein expression and metabolite levels are commonly measured using mass spectrometry (MS) or chromatography separations coupled with MS-based techniques [2]. Through a combination of measurements, specific biomolecular networks and molecular signatures of disease-states can be elucidated. To illustrate the scale of such studies, ca. 10 and 10 measurements were performed to generate a perturbation model of galactose metabolism in yeast and to determine a suite of prostate cancer biomarkers, respectively [2, 3]. Such large-scale experiments motivate the development of measurement strategies that incorporate higher throughput, higher selectivity, are comprehensive, and require minimal sample manipulation. Emerging developments in two-dimensional gas-phase separations on the basis of ion mobility–mass spectrometry (IM–MS) have demonstrated great promise for biomolecular separations of complex samples. This trend report focuses on several of the unique capabilities of IM–MS in contrast with MS-only strategies and provides a description of several key measurement areas in which IM–MS will likely play an increasing role in the near future. Detailed discussions of IM–MS techniques for biomolecular applications are provided elsewhere [4–9].