(Posted to Fairfield Citizen newspaper’s website w/o 12/20)
By Mike Lauterborn
© 2010. All Rights Reserved.
Fairfield, CT – A Moscow-born math professor with a knack for numbers has helped develop an algebraic tool that will help take the guesswork out of scientific experimentation and refine genetic research processes – a plus in the ongoing battle with cancer.
Newtown resident Vera Cherepinsky, Ph.D., Assistant Professor of Mathematics at Fairfield University, met with the Citizen News recently on the school’s campus to shed light on her inspiration and how the tool can help researchers.
“I was a family outlier,” said Cherepinsky, an emigrant to the U.S. from Russia in 1991. “My whole family was computer science oriented. I always liked math puzzles, and studying patterns. Math is really a study of patterns and how we organize them.”
Cherepinsky graduated from Polytechnic University in Brooklyn in 1998 and from Courant Institute of Mathematical Sciences at New York University in 2003. While she was a graduate student, she and her doctoral advisor, Dr. Bud Mishra, were hired to do consulting work by a bio-tech company called BioArray Solutions in Warren, NJ. The company had detected some results in the lab that they couldn’t explain.
Cherepinsky and Mishra focused on the problem together with BioArray researchers. Respectively, they brought to the table multi-disciplinary backgrounds including math, computer science, biology and physics.
As the professor explained, “The issue was that when two experiments were performed at the same time (in parallel), the results from each differed from the results when the experiments were done individually.”
The team labeled this anomaly “Competitive Hybridization” or the “Competition Effect” for short, and developed a mathematical model to explain the effect. It was validated using experimental data and can now be applied to predict this kind of interaction and used to design better experiments in many areas of biology, including cancer research.
“Some of the work that I did on this problem became a chapter of my doctoral dissertation,” said Cherepinsky. “Here at the university, I revisited it and brought it into publishable form.”
Why is this significant in a larger world view? “If you’re a cancer researcher interested in a particular gene, you can apply this tool to choose how you search for that gene,” she said. “A gene has a long sequence, measured in hundreds to thousands of DNA bases, and there are many possible short “snippets” you could use to search for it. Which of them should be used is a question in experiment design, which our model can help answer.”
The benefits overall are more efficient experimentation and more reliable answers. In a global view, this could result in tremendous research cost savings as it helps by “nipping in the bud” potential false positive and false negative errors in advance by predicting them in simulation.
The work of Cherepinsky and her colleagues, BioArray’s Ghazala Hashmi and NYU’s Mishra, has just been published in the scientific journal Physical Review E and, thus far, the reaction has been very positive. The journal’s parent organization, the American Physical Society, also included the paper in a November compilation of significant research developments in biological physics.
“Increasingly, problems in many areas dealing with the human genome require the collaboration of mathematicians and scientists from many related disciplines to adequately address biological dilemmas,” said Cherepinsky. It’s an exciting time with rapid discoveries that could ultimately help eradicate disease and major medical conditions that plague our world.
Cherepinsky reflected, “There’s a song by folk rock singer Catie Curtis that has a line that I take to heart. ‘If I can’t change the world, I’ll change the world within my reach,’ and I think that the work we’ve done here has addressed one piece of a larger puzzle.”