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Researchers propose a better way to make sense of 'Big Data'
Date:2/18/2014

e solution, they say, is a well known mathematical measure called "mutual information," first described in 1948. It was initially used to quantify the amount of information that could be transmitted electronically through a telephone cable; the concept now underlies the design of the world's telecommunications infrastructure. "What we've found in our work is that this same concept can also be used to find patterns in data," Kinney explains.

Applied to Big Data, mutual information is able to reveal patterns in large lists of numbers. For instance, it can be used to analyze patterns in data sets on the numerous bacterial species that help us digest food. "This particular tool is perfect for finding patterns in studies of the human microbiome, among many other things," Kinney says.

Importantly, mutual information provides a way of identifying all types of patterns within the data without reliance upon any prior assumptions. "Our work shows that mutual information very naturally solves this critical problem in statistics," Kinney says. "This beautiful mathematical concept has the potential to greatly benefit modern data analysis, in biology and in biology and many other important fields.


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Contact: Jaclyn Jansen
jjansen@cshl.edu
516-367-8455
Cold Spring Harbor Laboratory
Source:Eurekalert  

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