Kirschner, Denise EHunt, C AnthonyMarino, SimeoneFallahi-Sichani, MohammadLinderman, Jennifer J2015-01-052014Kirschner, Denise E, C Anthony Hunt, Simeone Marino, Mohammad Fallahi-Sichani, and Jennifer J Linderman. 2014. “Tuneable resolution as a systems biology approach for multi-scale, multi-compartment computational models.” Wiley Interdisciplinary Reviews. Systems Biology and Medicine 6 (4): 289-309. doi:10.1002/wsbm.1270. http://dx.doi.org/10.1002/wsbm.1270.1939-5094http://nrs.harvard.edu/urn-3:HUL.InstRepos:13581239The use of multi-scale mathematical and computational models to study complex biological processes is becoming increasingly productive. Multi-scale models span a range of spatial and/or temporal scales and can encompass multi-compartment (e.g., multi-organ) models. Modeling advances are enabling virtual experiments to explore and answer questions that are problematic to address in the wet-lab. Wet-lab experimental technologies now allow scientists to observe, measure, record, and analyze experiments focusing on different system aspects at a variety of biological scales. We need the technical ability to mirror that same flexibility in virtual experiments using multi-scale models. Here we present a new approach, tuneable resolution, which can begin providing that flexibility. Tuneable resolution involves fine- or coarse-graining existing multi-scale models at the user's discretion, allowing adjustment of the level of resolution specific to a question, an experiment, or a scale of interest. Tuneable resolution expands options for revising and validating mechanistic multi-scale models, can extend the longevity of multi-scale models, and may increase computational efficiency. The tuneable resolution approach can be applied to many model types, including differential equation, agent-based, and hybrid models. We demonstrate our tuneable resolution ideas with examples relevant to infectious disease modeling, illustrating key principles at work. WIREs Syst Biol Med 2014, 6:225–245. doi:10.1002/wsbm.1270 How to cite this article: WIREs Syst Biol Med 2014, 6:289–309. doi:10.1002/wsbm.1270en-USJournal Article2015-01-0510.1002/wsbm.1270