These days, a great deal of medical research is conducted using huge distributed databases, involving a large number of scientists, and often requiring computational power more than any one computer system can provide. To deal with these challenges, a technique called GRID computing is employed to harness the power of many computer systems to collectively deal with one task. Probably the most publicized of these projects is Folding@Home, but many others exist both publicly and within private institutions, while others are still in development. To bring people that work on these systems together, the field holds an annual HealthGrid meeting, and next year its coming to Chicago.
Many biomedical and health related problems are characterized by diverse collaborators needing access to great quantities of complex heterogeneous data, which is distributed across multiple computing systems, maintained by loosely connected institutions, often across international boundaries. Example projects addressing these challenges include sharing datasets to enable a cure for cancer (caBIG, ACGT) and science portals that enable neuroscientists to better visualize the morphology of the brain (BIRN). These and other projects have begun to demonstrate the power and potential of the Grid approach in biomedicine.
Initially, Grid technology development was driven by computing needs of the particle physics research community and enabled by the availability of high-performance networks. The term “grid” rapidly evolved toward a concept of ubiquitous and transparent computing to support a wide variety of applications, and builds on the well-known metaphor of the pervasive “electricity grid”. Today, the HealthGrid space represents some of the most interesting drivers for progress in knowledge-based ubiquitous and transparent computing.