Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

Researchers propose a better way to make sense of 'Big Data'

19.02.2014
New application of a classic concept challenges the latest statistical tools

Big Data is everywhere, and we are constantly told that it holds the answers to almost any problem we want to solve. Companies collect information on how we shop, doctors and insurance companies gather our medical test results, and governments compile logs of our phone calls and emails. In each instance, the hope is that critical insights are hidden deep within massive amounts of information, just waiting to be discovered.


Two researchers at Cold Spring Harbor Laboratory challenge the most recent advances in this Big Data analysis, using a classic mathematical concept to tackle the outstanding problems in this field. Mutual information is able to uncover patterns in large lists of numbers, revealing entirely new, unexpected patterns.

Credit: extradeda/Shutterstock

But simply having lots of data is not the same as understanding it. Increasingly, new mathematical tools are needed to extract meaning from enormous data sets. In work published online today, two researchers at Cold Spring Harbor Laboratory (CSHL) now challenge the most recent advances in this field, using a classic mathematical concept to tackle the outstanding problems in Big Data analysis.

What does it mean to analyze Big Data? A major goal is to find patterns between seemingly unrelated quantities, such as income and cancer rates. Many of the most common statistical tools are only able to detect patterns if the researcher has some expectation about the relationship between the quantities. Part of the lure of Big Data is that it may reveal entirely new, unexpected patterns. Therefore, scientists and researchers have worked to develop statistical methods that will uncover these novel relationships.

In 2011, a distinguished group of researchers from Harvard University published a highly influential paper in the journal Science that advanced just such a tool. But in a paper published today in Proceedings of the National Academy of Sciences, CSHL Quantitative Biology Fellow Justin Kinney and CSHL Assistant Professor Gurinder "Mickey" Atwal demonstrate that this new tool is critically flawed. "Their statistical tool does not have the mathematical properties that were claimed," says Kinney.

Kinney and Atwal show that the correct tool was hiding in plain sight all along. The 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.

The research described here was supported by the Simons Center for Quantitative Biology at Cold Spring Harbor Laboratory.

"Equitability, mutual information, and the maximal information coefficient" appears online in PNAS on February 17, 2014. The authors are: Justin Block Kinney and Gurinder Singh Atwal. The paper can be obtained online at: http://www.pnas.org/content/early/2014/02/14/1309933111.abstract

About Cold Spring Harbor Laboratory

Founded in 1890, Cold Spring Harbor Laboratory (CSHL) has shaped contemporary biomedical research and education with programs in cancer, neuroscience, plant biology and quantitative biology. CSHL is ranked number one in the world by Thomson Reuters for the impact of its research in molecular biology and genetics. The Laboratory has been home to eight Nobel Prize winners. Today, CSHL's multidisciplinary scientific community is more than 600 researchers and technicians strong and its Meetings & Courses program hosts more than 12,000 scientists from around the world each year to its Long Island campus and its China center.

Jaclyn Jansen | EurekAlert!
Further information:
http://www.cshl.edu

More articles from Information Technology:

nachricht The app for frequent fliers and those who are radiation-conscious
15.04.2015 | Physikalisch-Technische Bundesanstalt (PTB)

nachricht Passenger-focused air conditioning
14.04.2015 | Technische Universitaet Muenchen

All articles from Information Technology >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Astronomers reveal supermassive black hole's intense magnetic field

Astronomers from Chalmers University of Technology have used the giant telescope Alma to reveal an extremely powerful magnetic field very close to a supermassive black hole in a distant galaxy

Astronomers from Chalmers University of Technology have used the giant telescope Alma to reveal an extremely powerful magnetic field very close to a...

Im Focus: A “pin ball machine” for atoms and photons

A team of physicists from MPQ, Caltech, and ICFO proposes the combination of nano-photonics with ultracold atoms for simulating quantum many-body systems and creating new states of matter.

Ultracold atoms in the so-called optical lattices, that are generated by crosswise superposition of laser beams, have been proven to be one of the most...

Im Focus: UV light robot to clean hospital rooms could help stop spread of 'superbugs'

Can a robot clean a hospital room just as well as a person?

According to new research out of the Texas A&M Health Science Center College of Medicine, that is indeed the case. Chetan Jinadatha, M.D., M.P.H., assistant...

Im Focus: Graphene pushes the speed limit of light-to-electricity conversion

Researchers from ICFO, MIT and UC Riverside have been able to develop a graphene-based photodetector capable of converting absorbed light into an electrical voltage at ultrafast timescales

The efficient conversion of light into electricity plays a crucial role in many technologies, ranging from cameras to solar cells.

Im Focus: Study shows novel pattern of electrical charge movement through DNA

Electrical charges not only move through wires, they also travel along lengths of DNA, the molecule of life. The property is known as charge transport.

In a new study appearing in the journal Nature Chemistry, authors, Limin Xiang, Julio Palma, Christopher Bruot and others at Arizona State University's...

All Focus news of the innovation-report >>>

Anzeige

Anzeige

Event News

HHL's Entrepreneurship Conference on FinTech

13.04.2015 | Event News

World Conference On Regenerative Medicine 2015: Registration And Abstract Submission Now Open

25.03.2015 | Event News

University presidents from all over the world meet in Hamburg

19.03.2015 | Event News

 
Latest News

Engineer Improves Rechargeable Batteries with MoS2 Nano 'Sandwich'

17.04.2015 | Power and Electrical Engineering

Comparing Climate Models to Real World Shows Differences in Precipitation Intensity

17.04.2015 | Earth Sciences

A blueprint for clearing the skies of space debris

17.04.2015 | Physics and Astronomy

VideoLinks
B2B-VideoLinks
More VideoLinks >>>