Researchers at the San Diego Supercomputer Center are studying cell stress — but instead of using high-performance computing hardware, which includes their local CTBP cluster and the Triton supercomputer, the team opted for good old fashioned grid computing.
The project, led by Nick Schafer, a biophysicist in the Wolynes group at the Center for Theoretical Biological Physics at University of California-San Diego, needed some serious high-performance computing power to study NF-kappaB and I-kappaB proteins, which are both implicated in cell stress response.
In order to study the phenomenon known as "misregulation" which occurs when NF-kappaB and I-kappaB are not working properly, thousands of molecular simulations have to be run, which requires more computational muscles than SDSC had to offer locally.
“Many of our simulations can be run efficiently on a single processor but require many of these simulations to run simultaneously, which makes OSG particularly well suited to our purposes,” Schafer said. “We have had recent technical advances which, combined with the OSG resources, should allow us to move faster than ever towards determining which specific structural aspects are important in the interactions between NF-kappaB, I-kappaB and DNA.”
Their solution was to add the Open Science Grid (OSG) to their HPC arsenal. The OSG is a network of distributed computing resources for scientific research headed up by the Open Science Grid Consortium, an organization composed of service and resource providers. Members independently manage their own resources and the consortium proves the framework for integration.
The OSG currently offers users a range of toolkits specifically for biology and medical research, including the Geant4 software Toolkit, the Grid Laboratory of Wisconsin, the nanoHUB Network for Computational Nanotechnology, and the Structural Biology Grid.