A better understanding of epigenetics, or changes in our genetic activity that do not precipitate changes in our genetic code, is one of outcome of expanded research capabilties. As technology gets more refined, broadening possibilities for scientific investigation and, indeed, our ability to inquire into the nature of things, our best researchers gain new insights on a range of questions, conditions and phenomena. This of course includes the latest in electron micrscopy and advanced clinical trials but also mathematical and statistical modeling techniques that increasingly hold the key to advanced analysis and identification:
[A] statistics researcher has been awarded a $1.44 million grant from the National Institutes of Health to develop statistical models that may one day be used to predict cancer and other diseases.
Wenxuan Zhong, an associate professor in the Franklin College of Arts and Sciences department of statistics, will use the funds to develop predictive statistical models based on epigenetic change patterns.
Epigenetics—epi meaning ‘over' or ‘other' in Greek—is the study of changes in a gene's behavior that can be passed down without actually altering the genetic code. Like an airport traffic controller, the epigenome passes along instructions that change the way the gene is expressed by switching genes on and off.
Zhong hopes to shed light on the role of epigenetic changes in illnesses, particularly cancer.
One form of epigenetic change known as DNA methylation is particularly understudied in this area.
"There's a large amount of evidence that a process known as DNA methylation is a key player in cancer development," Zhong said. "Today's next-generation sequencing techniques give us the data we need to close the gap in this area of research."
Zhong and her team will develop a suite of statistical models to broaden the understanding of how epigenetic patterns are established and maintained during normal development and under different environmental conditions.
Large amounts of epigenetic and genomic data are routinely collected, processed and stored. Statisticians like Zhong look for ways to make the data tell the story.
Congratulations to Dr. Zhong and her team on this new support for an important path of inquiry. These pursuits represent the very best of university research and the leading edge of scientific discovery.