Agilent Cuts Through Big Data in Biology

Until the 20th century, the world’s information doubled every 100 years.  By the end of World War II, it was doubling every 25 years.  With the rise of the Internet, inexpensive storage and emerging economies, information is currently doubling every year.  IBM predicts it may soon double every 12 hours.

This is especially a challenge in life sciences, where clinical knowledge is currently doubling every 18 months.  It is possible that many of today’s biggest challenges – from disease treatments to longevity to global warming – could be addressed by analyzing data that already exists.  But so much is being generated today that many vital pieces of information are never even looked at by a human being.

Dr. John McLean is trying to do something about the challenge of “big data,” which is measured in three dimensions: volume, velocity and variety.  The chemist and his team at Vanderbilt University are using an Agilent 6560 Ion Mobility Q-TOF LC/MS system to gather details of 50,000 molecules per minute in untargeted experiments.

In the same way that companies such as Amazon and Netflix mine customer data to determine consumer buying habits, McLean hopes to find patterns in biological data.  He describes his team’s approach as “integrated omics.”

“We’re breaking the old paradigm of individual omics studies – genomics, proteomics and so on,” McLean says.  “We’re now able to go into a biological question with or without having a target in mind.  We can let the analysis tell us what we should be paying attention to.”

As an example, McLean is studying various bacteria in 10,000 caves throughout Tennessee and Kentucky, some of which have never had contact with humans before, in the hopes of developing new drug molecules.

“All this big data stuff, it’s all the same game,” McLean says. “What are the patterns? Once you remove the descriptors from the data, it’s just a huge series of numbers. Then it depends on who’s looking at the numbers and knows what generated them. It doesn’t matter if you’re in Internet commerce or trying to solve biology. It’s all the same thing.”


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