December 22, 2014

Scrolling Headlines:

Recovery fund established for former UMass student Chloe Rombach -

Sunday, December 21, 2014

Minutemen search for answers following blowout loss to Providence -

Saturday, December 20, 2014

UMass dominated in 85-65 loss to Providence -

Saturday, December 20, 2014

BLOG: UMass football recruiting roundup: UMass signs DT, offers two kickers -

Wednesday, December 17, 2014

UMass President Robert Caret resigns to become chancellor of the University of Maryland system -

Wednesday, December 17, 2014

Brandon Montour: ‘It felt great to be out there’ -

Wednesday, December 17, 2014

UMass falls to Northeastern in Brandon Montour’s debut -

Tuesday, December 16, 2014

Cady Lalanne continues to evolve as a potential outside shooting threat -

Tuesday, December 16, 2014

UMass hockey returns to action against Northeastern, Montour to make season debut -

Tuesday, December 16, 2014

Demetrius Dyson remains hopeful despite rocky start to season -

Tuesday, December 16, 2014

Former UMass soccer star Matt Keys aims to continue his career professionally -

Monday, December 15, 2014

Pierre-Louis, Dillard shine in UMass victory over Holy Cross -

Sunday, December 14, 2014

Passing, spacing improved in UMass victory -

Saturday, December 13, 2014

Prolific first half propels UMass past Canisius, 75-58 -

Saturday, December 13, 2014

UMass Faculty Senate hears ad hoc committee’s report on FBS football, shoots down contentious motion -

Thursday, December 11, 2014

Minutemen hope improved spacing will aid struggling half court offense -

Wednesday, December 10, 2014

Divest UMass urges Board of Trustees to split with fossil fuel industry -

Wednesday, December 10, 2014

Cady Lalanne accustomed to dealing with increased attention -

Tuesday, December 9, 2014

Front to Back: Week of Dec. 1, 2014 -

Monday, December 8, 2014

Chiarelli: UMass basketball running out of time to find its identity -

Monday, December 8, 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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