Parallel computing for adaptive multi-cellular gene network modeling

Understanding how gene regulatory networks, which adapt to changing environment at the single-cell level, define cell population behavior via self-organization is an interesting yet challenging research topic. Previously, we have shown that such self-organizing multi-cellular behavior can be modeled and predicted by an adaptive gene network model. In the natural world, many (including biological) events are happening simultaneously and parallel computing is better suited for modeling real world phenomena, compared to serial computing. In this article, it is suggested that a parallel computing scheme, which represents individual cells as high performance computing nodes, can be a useful tool for simulating self-organizing multi-cellular behavior in a more realistic way.