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Pentagon looking for 'Big Mechanism' to mine health data

Feb. 3, 2014 - 06:00AM   |  
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The Pentagon is planning to embark on a $45 million data mining program, which it calls a “Big Mechanism,” to track research into the biology of cancer and signal pathways for cancer cells.

An announcement released recently by the Defense Advanced Research Projects Agency (DARPA) shows the program hopes to comb through the growing trove of worldwide scientific research to find specific terms related to cancer and assemble them into a more coherent package that will allow researchers to better understand the latest developments.

Medical researchers have searched for years for a system that can find information located in various reports and combine it into one place. The philosophy behind the Big Mechanism is for researchers to be able to find new information found in the various scientific reports and papers published around the world and then absorb that information into their ongoing work.

The program is an example of bioinformatics, which involves managing, mining and interpreting information included in biological reports and data.

Officials and researchers throughout the government have been targeting ways to examine more data to find treatments for various medial ailments or to track inventions that have the potential to disrupt U.S. military efforts. The Pentagon has launched a new project called Technology Watch/Horizon Scanning, which aims to track developing technologies around the world that could either aid U.S. military efforts or seriously disrupt existing military plans.

The DARPA announcement seeks researchers from universities, government and private industry to propose how to build the mechanism and weave data mining into ongoing research. One government-affiliated think tank and contractor, the MITRE Corp. of Bedford, Mass., is a leader in data mining research.

By the final 12 months of the project, DARPA documents show, mechanism developers should be able to identify targets for therapy based on their findings in the data.

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