Biomedical Engineering Reference
In-Depth Information
On the Horizon
The availability of affordable, powerful computer hardware and software affects more than simply the
throughput of modeling and simulation experiments in bioinformatics. A common finding in
simulation-based R&D is that as more computer processing power becomes available, the time
required to run a simulation doesn't decrease significantly. Instead, researchers tend to increase the
complexity of the underlying models in order to provide higher-resolution—and presumably more
realistic—simulations. This phenomenon is most obvious in the motion picture industry in which
computer-animated figures, which are based on models of synthetic characters, have become
virtually indistinguishable from real actors. For example, the T-1000 robot in Terminator II , the first
use of a simulated actor in a major motion picture, is virtually indistinguishable from a human actor.
Similarly, in the life sciences, increased access to computing power is resulting in the development
and use of more complex, higher-resolution models and simulation systems. This is critical, because
inadequate resolution can lead to incorrect conclusions. For example, a model of protein-protein
interaction that doesn't take temperature, pH, and the presence or absence of sugars and other
molecules in the local environment into consideration may incorrectly predict a level of interaction
that wouldn't be possible in reality.
Work is underway to develop increasingly complex modeling and simulation software that is designed
to use the ever-present next-generation of desktop computer hardware and operating systems.
There is also considerable activity in the areas of heuristic control of simulations, as well as
advancing cluster, grid, and mainframe computing. This power is being directed at rapid computation
and is enabling researchers to consider additional phenomena that are relevant to the structure and
function of proteins, such as the role of functional glycomics, for example. Approaches to realizing
more computational throughput includes making existing simulation code parallel so that it can make
use of multiple processors, and of special, high-performance mainframe hardware architectures used
by IBM's SP-2 Blue Gene, and similar machines.
 
 
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