Scrolling Headlines:

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June 17, 2017

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May 18, 2017

UMass basketball’s Donte Clark transferring to Coastal Carolina -

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Report: Keon Clergeot transfers to UMass basketball program -

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Despite title-game loss, Meg Colleran’s brilliance in circle was an incredible feat -

May 14, 2017

UMass softball loses in heartbreaker in A-10 title game -

May 14, 2017

Navy sinks UMass women’s lacrosse 23-11 in NCAA tournament second round, ending Minutewomen’s season -

May 14, 2017

UMass softball advances to A-10 Championship game -

May 13, 2017

UMass basketball adds Rutgers transfer Jonathan Laurent -

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UMass women’s lacrosse gets revenge on Colorado, beat Buffs 13-7 in NCAA Tournament First Round -

May 13, 2017

Meg Colleran dominates as UMass softball tops Saint Joseph’s, advances in A-10 tournament -

May 12, 2017

Rain keeps UMass softball from opening tournament play; Minutewomen earn A-10 honors -

May 11, 2017

Former UMass football wide receiver Tajae Sharpe accused of assault in lawsuit -

May 10, 2017

Justice Gorsuch can save the UMass GEO -

May 10, 2017

Minutemen third, Minutewomen finish fifth in Atlantic 10 Championships for UMass track and field -

May 8, 2017

UMass women’s lacrosse wins A-10 title for ninth straight season -

May 8, 2017

Dayton takes two from UMass softball in weekend series -

May 8, 2017

Towson stonewalls UMass men’s lacrosse in CAA Championship; Minutemen season ends after 9-4 loss -

May 6, 2017

Zach Coleman to join former coach Derek Kellogg at LIU Brooklyn -

May 5, 2017

UMass men’s lacrosse advances to CAA finals courtesy of Dan Muller’s heroics -

May 4, 2017

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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