Joining the medical research fold

The lab primarily uses computer simulations to study protein folding during its formation and misfolding which can lead to diseases. The computer simulations require a massive amount of computing power. A protein folds in tens of microseconds and it takes the average computer CPU approximately a day to simulate a nanosecond – or 30 CPU years to simulate the full folding process.


The Pande lab has solved the computing problem by dividing the work between a distributed network of computers around the world. Anyone with a reasonably new computer can join the project, effectively donating computer processing power to the lab when the computer is idle. The network presently has 390 000 active CPUs with over 8 million registered CPUs. By comparison, a supercomputer has in the order of 15 000 CPUs. To date the calculations have lead to no less than 96 peer-reviewed scientific papers, with the latest papers providing significant inroads towards designing new small molecule drug candidates for treating amyloidosis and Alzheimer’s Disease.


Australian Marine Ecology has substantial computing power for ecological and population growth modelling, large dataset multivariate statistical analysis, neural network development and processing hydroacoustics, including correcting and mosaicing sidescan sonar data. Specifically, we have an nVidia Tesla general processing GPU (graphics processing unit). This GPGPU has the equivalent of 450 CPU cores for parallel processing, but has been idle most days of the week – until now. When not working for us, the GPGPU now accepts work units from the Folding@Home project, runs a set of simulations in the background and sends the results back to Stanford University.


To date, our contributions are meagre compared to other donors around the world, but we are proud to be part of this massive system that is solving crucial medical and scientific problems. You can follow our contributions on the Folding@Home project webpage – just look up the team: Aus_Marine_Ecology (team number 218198).

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