Mathematicians and researchers from NYU’s Courant Institute of Mathematical Sciences have discovered a new model to apply mathematics to measure cellular activity through biotechnology.
Using algebra, researchers created a model to imitate DNA-duplex formation. With the model, they applied algebraic computations to see how different DNA strands match up, using a “tagging” system.
By assigning variables, or “tags,” to specific chemical properties, they identified specific genes or DNA matches.
The co-authors, Vera Cherepinsky, Ghazala Hashmi and Bud Mishra, said the research allows observation of genes and demonstrates how tags affect other genes — a new breakthrough in biotechnology.
Some experts, however, have more skeptical sentiments about the research. One member of the biology department who requested anonymity questioned the research.
“Sure, the research is sound, but this is nothing new,” the faculty member said. “Many groups before have applied the same kind of theories. There isn’t much utility in the research.”
Other members of the biology department declined to comment, some out of fear of losing their jobs.
Cherepinsky, researcher in the department of mathematics and computer science at Fairfield University, said the research may aid future experiments.
“I think the utility lies in allowing people designing the experiment to detect in advance the probes that would interfere with each other’s signal,” she said.
Although Cherepinsky said the research has potential benefits, she added that it is still in its beginning stages.
“Of course, there is a lot of work left to be done to determine precisely how our competitive hybridization models should be used to improve experiment design,” she said.
Mishra, a computer science and mathematics professor at Courant, agreed with Cherepinsky, and said the biology department faculty member had no foundation for his claims.
“The paper has been published in a well-regarded journal after peer review,” he said. “To be fair, I seriously doubt that the biology department has suitable expertise to be able to raise doubts about the utility of our findings. The model helps not just better measurements of cellular activities, but also improves the design of the underlying biotechnology.”