Parallel computing for cancer research

The National Cancer Institute’s Pediatric Oncology Branch is using parallel computing software to accelerate medical discoveries.

Interactive Supercomputing's (ISC) Star-P software will allow scientists to make use of powerful high performance computers to mine vast public databases to provide insight into the genetic risk factors for cancer, foster new procedures for testing tumours, or even identify genetic changes resulting from treatment.

The researchers use a Matlab-based application called CORR4DM to correlate one genomic array against a database of 100,000 parts of a gene, in search of specific DNA components or attributes. The results help them to understand the relationship between the genes, and may even direct future genomic research.

Once the sample sizes grew to consist of tens of thousands of arrays, it became obvious parallel computing was necessary to provide larger correlations.

'Running a single correlation on a desktop computer could take a week or more to complete,' said Bill Strecker, chief technical officer at ISC. 'An explosion in the amount of genomic data available to researchers has made their work increasingly difficult. Their tasks require more computing power, more system memory, and - all too often - more time. And in the race to understand how genetics and cancer are linked, time is precious.'

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