IBM's largest and fastest commercial supercomputer will unravel the hidden mysteries inside DNA to help a bio-informatics company investigate how genes interact in the human body to cause life-threatening diseases.

The supercomputer, which is capable of performing 7.5 trillion calculations per second and is 600 times faster than the IBM system that defeated chess champion Gary Kasparov in 1997, will be utilised by NuTec Sciences, which specialises in algorithms devoted to speeding up computations related to the human genome project.

The cluster of computers will consist of 1250 IBM servers supported by 2.5 terabytes of memory, 50 terabytes of online disk storage running IBM's DB2 Universal Database, and a high-bandwidth networking infrastructure.

The only machine that is faster is the ASCI White, a US government-owned machine at Lawrence Livermore Laboratories.

In collaboration with the National Human Genome Research Institute (NHGRI), part of the National Institutes of Health, NuTec will use the new system to distribute NIH-patented algorithms for analysing gene combinations which cause disease.

These algorithms can help researchers to enlist the right patients in clinical trials and predict outcomes which enable targeted therapies to be developed in less time and at a lower cost.

Dr Andy Baxevanis, director of computational genomics at the NHGRI, said: "The ability to scan thousands of genes at one time has been of great value, particularly in trying to deduce the critical differences in gene expression between a normal and a diseased cell."

He added that by developing new software aimed at detecting and understanding the differences "we will be able to make exciting biological discoveries and find new ways to apply these technologies to patient care".

Big Blue will work with NuTec to develop applications that give medical researchers access to the NIH algorithms from their desktop computers. NuTec will lease time on the IBM system to academic research centres and biotechnology and pharmaceutical companies, as well as provide enhanced computational capabilities for smaller biotech startups.