Unfortunately, some of these problems require knowledge in areas of the biomedical spectrum that aren't necessarily available to traditional techniques. To overcome these and other hurdles, it is crucial that biomedical scientists include state-of-the-art computational techniques in their arsenal of research tools. Probably even more importantly, researchers must continue to push the envelope of algorithm and simulation development in the quest for understanding.
As with those in most fields in which simulation is relied on, biomedical scientists have identified major areas of computational technology for targeted improvement efforts in the coming years. Not surprisingly, the computational goals of these researchers fall in line with those of other simulation workers. In particular, the main focus for improvement will be on performing simulations over a larger time scale, increasing the size of systems which can be realistically and feasibly simulated, improving the quality of structural predictions for biochemical species and combining classical and quantum chemical computational techniques in simulation studies. These points have been discussed in this space before in the context of other areas of study, but a brief review of their importance is illustrative.
The time scale of a simulation will probably always be a limiting factor. Many biological processes happen on a scale of milliseconds to seconds, if not longer. While these time slices may seem tiny to humans, they are literally almost an eternity to time-dependent simulation techniques, which often utilize timestep on the order of a femtosecond (1 second = 1,000,000,000,000,000 femtoseconds!). In order to examine some of the most interesting biomedical problems, the accessible time scale needs to be beefed up through a combination of increased hardware power, utilization of parallel computing techniques and improved algorithms.
Closely related to the issue of time scale is the size of the
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