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March 28, 2012

Spinning Data into Super Plants

Robert Gelber

As the world population grows, more stress is put on the earth’s natural resources. Most notably, food supplies need to increase to match human demand. At the University of Missouri, researchers are looking to answer these challenges through big data analysis.

U of M is a hub for both medical and agricultural genetics research. Last week, Dr. Gordon Springer, associate professor within the university’s computer science department and director of the university’s bioinformatics consortium discussed specific big data driven projects underway at U of M, emphasizing a rather unique use case for large data sets.

Researchers at U of M are culling the massive genetic sets for genes that can increase the resiliency of plants, allowing them to exist in drought conditions or withstand bugs and other pests. These include corn and wheat crops as well as soybeans. Such research could effectively create “super plants”—potentially spawning a revolution in terms of world hunger.

Springer says that dealing with data at the scale of genetics is a great challenge, but that there are some unique tools that are helping his researchers contend with the deluge. As he stated:

Isilon at U of M“The amount of data that is generated by mechanical means these days is just absolutely enormous. Just here at the university, we generate something on the order of about five to six terabytes of data per week, all of which needs to be analyzed. It can’t be analyzed by hand because nobody can read that much data even in a week’s time.” ; ;

To help capture and explore the information generated by their research, UM recently partnered with neighboring vendor Appistry Inc.

The St. Louis company offers a Life Sciences platform called Ayrris/BIO, a product focused on Next-Gen Sequencing (NGS) analysis and has a historically close relationship with research efforts at the university. Springer said software tools from the company have reduced the amount of time required for processing research data.

As far as technology at the university was concerned, Lundquist was curious if Springer considered it cloud architecture. ; He did, however, didn’t seem to put too much focus on the nomenclature.

“In our case we have taken the cloud and brought it inside our house.” He continued, “The software that we have, and are using along with that, improves the ability to run data analyses in parallel, which has not been done in previous times.” This would explain the increased speed in data processing.

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