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Biological system behaviors are often the outcome of complex interactions among a
large number of cells and their biotic and abiotic environment. Computational biologists
attempt to understand, predict and manipulate biological system behavior through mathematical
modeling and computer simulation. Discrete agent-based modeling (in combination with
high-resolution grids to model the extracellular environment) is a popular approach
for building biological system models. However, the computational complexity of this
approach forces computational biologists to resort to coarser resolution approaches
to simulate large biological systems. High-performance parallel computers have the
potential to address the computing challenge, but writing efficient software for parallel
computers is difficult and time-consuming.
Computational Biology and Bioinformatics Group, High-performance Computing Group,
Pacific Northwest National Laboratory, Richland, WA 99354, USA, Department of Computer
Science, Utah State University, Logan, UT 84322, USA and Institute for Systems Biology,
Seattle, WA 98109, USA.