November 27, 2014

Scrolling Headlines:

UMass basketball trounces Northeastern 79-54 -

Wednesday, November 26, 2014

Students and staff discuss racial and social inequality following Ferguson decision -

Wednesday, November 26, 2014

UMass hockey falls to Vermont, 3-1 -

Wednesday, November 26, 2014

No indictment for Ferguson cop -

Tuesday, November 25, 2014

Chancellor addresses campus regarding grand jury decision in death of Michael Brown -

Tuesday, November 25, 2014

Northern Illinois hangs on against Ohio, Hunt carries Toledo to victory -

Tuesday, November 25, 2014

SGA passes 10 motions at meeting Monday night -

Tuesday, November 25, 2014

Students and UMPD work together during the annual ‘Walk for Light’ -

Tuesday, November 25, 2014

‘Conscious Consumer’ talk promotes business sustainability -

Tuesday, November 25, 2014

UMass hockey looks to rebound against Vermont following Saturday’s blowout at home -

Tuesday, November 25, 2014

UMass women’s soccer’s Sverrisdóttir balances a soccer career between two different countries -

Tuesday, November 25, 2014

‘First Demo’ provides a fascinating glimpse of Fugazi in its infancy -

Tuesday, November 25, 2014

My mental illness does define me (to an extent) -

Tuesday, November 25, 2014

How to master multitasking -

Tuesday, November 25, 2014

One Direction hints at newfound sophistication on ‘Four’ -

Tuesday, November 25, 2014

TV on the Radio sounds rejuvenated on ‘Seeds’ -

Tuesday, November 25, 2014

UMass men’s club soccer fundraises its way to Memphis -

Tuesday, November 25, 2014

UMass hockey takes accountability and seeks redemption against Vermont on Tuesday -

Tuesday, November 25, 2014

Large group of males tries to forcibly enter a Hobart apartment over the weekend -

Tuesday, November 25, 2014

UMass forward Zach Coleman excels in increased role against Florida State -

Monday, November 24, 2014

UMass study reveals genetic links with disease

Chris Roy/Collegian

A new approach to data analysis has led University of Massachusetts biostatisticians to discover new genetic information linked to common diseases such as diabetes and heart disease, according to a UMass press release.

The team of researchers, led by Andrea Foulkes, has applied this new approach to data analysis to pre-existing databases, revealing the genetic information behind that which causes conditions such as high cholesterol and heart diseases, according to the release.

Foulkes directs the Institute for Computational Biology, Biostatistics and Bioinformatics at UMass. Other members of her team include Rongheng Lin, an assistant professor, and Gregory Matthews and Ujjwall Das, who are both postdoctoral researchers. The work done by the team was supported by the National Institutes of Health National Heart, Lung and Blood Institute, the release stated.

“This new approach to data analysis provides opportunities for developing new treatments. It also advances approaches to identifying people at greatest risk for heart disease,” said Foulkes in the release.

The new style of analysis coined “MixMAP,” which was developed by Foulkes and cardiologist Dr. Muredach Reilly at the University of Pennsylvania, stands for “Mixed modeling of Meta-Analysis P-values,” according to the release. Since this method of statistical analysis is based on pre-existing public information, it “represents a low-cost tool” for researchers, according to the release.

“Another important point is that our method is straightforward to use with freely available computer software and can be applied broadly to advance genetic knowledge of many diseases,” Foulkes added in the release.

Foulkes explained that the new method takes the entire human genome into account and can be generalized to figure out many different diseases. Though the other more widely-used methods of gene tracking and analysis look for a “needle in a haystack,” so to speak, as a disease signal, according to the release, Foulkes’ new method makes use of genome knowledge in DNA regions that “contain several genetic signals for disease variation clumped together. … Thus, it is able to detect groups of unusual variants.”

According to the release, Foulkes characterizes the “MixMAP” technique as a discovery method still in need of scientific validation, although it “goes farther than usual by using sophisticated modeling approaches to quantify error.”

“We’ve done better than simply identify the strongest signals, we’ve quantified measures of association to show they are statistically meaningful,” noted Foulkes in the release.

George Felder can be reached at gfelder@student.umass.edu

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