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For decades, researchers have been applying computer simulation to addressproblems in biology. However, many of these "grand challenges" in computationalbiology, such as simulating how proteins fold, remained unsolved due to theirgreat complexity. Indeed, even to simulate the fastest folding protein wouldrequire decades on the fastest modern CPUs. Here, we review novel methods tofundamentally speed such previously intractable problems using a newcomputational paradigm: distributed computing. By efficiently harnessing tensof thousands of computers throughout the world, we have been able to breakprevious computational barriers. However, distributed computing brings newchallenges, such as how to efficiently divide a complex calculation of many PCsthat are connected by relatively slow networking. Moreover, even if thechallenge of accurately reproducing reality can be conquered, a new challengeemerges: how can we take the results of these simulations (typically tens tohundreds of gigabytes of raw data) and gain some insight into the questions athand. This challenge of the analysis of the sea of data resulting fromlarge-scale simulation will likely remain for decades to come.

Folding@Home and Genome@Home: Using distributed computing to tackle previously intractable problems in computational biology