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New computing model could lead to quicker advancements in medical research, according to Virginia Tech
Date:11/4/2013

With the promise of personalized and customized medicine, one extremely important tool for its success is the knowledge of a person's unique genetic profile.

This personalized knowledge of one's genetic profile has been facilitated by the advent of next-generation sequencing (NGS), where sequencing a genome, like the human genome, has gone from costing $95,000,000 to a mere $5,700. So, now the research problem is no longer how to collect this information, but how to compute and analyze it.

"Overall, DNA sequencers in the life sciences are able to generate a terabyte--or one trillion bytes--of data a minute. This accumulation means the size of DNA sequence databases will increase 10-fold every 18 months," said Wu Feng of the Department of Computer Science in the College of Engineering at Virginia Tech.

"In contrast, Moore's Law (named after Intel co-founder Gordon E. Moore) implies that a processor's capability to compute on such 'BIG DATA' increases by only two-fold every 24 months. Clearly, the rate at which data is being generated is far outstripping a processor's capability to compute on it. Hence the need exists for accessible large-scale computing with multiple processors though the rate at which the number of processors needs to increase is doing so at an exponential rate," Feng added.

For the past two years, Feng has led a research team that has now created a new generation of efficient data management and analysis software for large-scale, data-intensive scientific applications in the cloud. Cloud computing is a term coined by computing geeks that in general describes a large number of connected computers located all over the world that can simultaneously run a program at a large scale. Feng announced his work in October at the O'Reilly Strata Conference + Hadoop World in New York City.

By background to Feng's announcement, one needs to go back more than three years. In April of 2010, the National Science Fo
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Contact: Lynn Nystrom
tansy@vt.edu
540-231-4371
Virginia Tech
Source:Eurekalert  

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