Data Crunching Made Easy

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: Uncovering new ways to treat diseases from increasing biological data remains a daunting task for a life sciences researcher. With new drugs taking years of resource-intensive research, development, testing and marketing, researchers at pharmaceutical and biotech companies must ensure that processes are completed as quickly, accurately, and inexpensively as possible. Thankfully, high performance computing (HPC) is coming to their rescue by allowing them to analyse massive amounts of data for genome analysis and drug design more quickly and cost effectively.

The Council of Scientific and Industrial Research (CSIR) centre for high performance computing in New Delhi hosts a four-teraflop Hewlett-Packard supercomputer at its facility in New Delhi, running the Linux operating system to advance its life sciences computational biology research.

“This is the among the most powerful HP supercomputer in Asia and vaults the centre into the ranks of global research institutions such as Pacific Northwest National Laboratory, Pittsburgh Supercomputing Centre, Sandia National Laboratory and Los Alamos National Laboratory that have implemented scaleable, multi-teraflop supercomputing systems,” says HP India Enterprise Business marketing and growth initiatives head, Faisal Paul.

The scientific exploration ranges from genes to proteins and from biotechnology to pharmaceuticals and personalised medicine. “They now possess multiple whole genomes to look for differences and similarities between all the genes of multiple species. From such studies, we can draw particular conclusions about species and general ones about evolution—often referred to as comparative genomics,” informs Paul.

Not far away, the supercomputing facility for bioinformatics and computational biology at the Indian Institute of Technology Delhi is serving 4,000 researchers worldwide to reduce computational time on complex research projects for genome analysis, protein structure prediction and drug design. The facility uses its high performance computing infrastructure for biomolecular modeling and creating new software used as tools for genome/protein structure based medicine development. The facility has an aggregate compute power of more than 600 Gflops and data storage capacity of 4 terabytes.

“We have taken on major challenges in genome analysis, protein folding and drug design research,” says the facility’s coordinator, B Jayaram. Going forward, the facility wants more insight into bigger problems such as annotating and categorising the human genome, automated protein structure prediction and lead molecule discovery.