Dr. Tingting Zhao has dedicated his research to developing new tools for processing the world around us. Applying her skill set to health science, she finds ways to use her cutting-edge data science skills to help others. “This is a topic that I’m really passionate about. The idea that something I was able to work on might one day make life easier for patients,” Bryant University Behavioral Sciences.
Her recent publication, “Identification of Key Gene Expression Alterations in Multiple Perturbation Experiments Using Knockoff,” provides insight into how research in biology and data science can extend to each other to great effect. offers. Using machine learning, a field of artificial intelligence and computers her science focuses on using data and algorithms to mimic the way humans learn, Zhao and co-workers found that genes respond to specific stressor stimuli. We have developed and refined an algorithm that helps us identify how we react to. Those responses were then compared to the effects of various ‘small molecule’ drugs.
Zhao was the first author of this paper. Her co-authors include Harsh Vardhan Dubey. Statistics student at the University of Massachusetts Amherst. Guangyu Zhu is an assistant professor in the Department of Computer Science and Statistics at the University of Rhode Island. His Patrick Flaherty, associate professor of mathematics and statistics at the University of Massachusetts Amherst, said:
“This is a very rapidly evolving field and there is a lot of competition as people around the world want the next breakthrough.”
The information discovered through their research will help us better understand the molecular pathways that respond to genetic and environmental changes, as well as the underlying mechanisms of disease. Zhao is particularly excited about the algorithm’s potential for drug diversion. “It takes a lot of effort and money to develop and approve new drugs,” he explains Zhao. “We want to investigate whether cheaper existing drugs can be used for new purposes, such as using them in place of more expensive drugs.”
This research is part of the growing field of bioinformatics, an interdisciplinary space involving the development of methods and tools for understanding biological data, with applications to understanding health, disease, and medicine. . Her focus on her health adds greater purpose to her data and her science work, she says. “We are not just developing algorithms in isolation,” she says. “We develop these technologies to solve real problems, and that problem should always motivate the people doing this work. “about it.”
According to her, the rise of the bioinformatics field speaks to greater adoption of computational analysis in the health sciences. “People’s opinions change with the times. Initially, there was some skepticism about this kind of research because it was not only biological, but it was also very computational,” she said. say. “But over time, people have become more comfortable using it because they have come to understand how useful these tools are.”
Today, bioinformatics is a hotbed of research. “There is a lot of competition because this is a very rapidly evolving field and people all over the world want the next breakthrough.” There is a thrill in knowing
But while healthy competition can spur innovation, Zhao said, ultimately collaboration is the real goal. “You always want others to use your research, make their own improvements, and help more people,” she recalls.