Priyanka Mehra, who recently earned her PhD in Microdata Analysis, used advanced computer models to study how genes interact during evolution. She focused on two key aspects: how genes influence one another and how a single gene can affect several traits at once. This genetic interaction, she found, determines how well a population can adapt to environmental changes – or withstand them.
– You can think of evolution as a gear shift. In calm, steady conditions, you stay in the same gear and run smoothly. But when the environment changes quickly, you need to shift gears so that the genes can work in new ways, find solutions, and survive, says Priyanka Mehra.
Her findings could have wide-ranging applications. They might help scientists predict how viruses and bacteria develop resistance to medicines, design more targeted and personalised treatments for diseases, and build smarter algorithms in artificial intelligence that learn and adapt like nature does.
– My research is really about life’s ability to adapt. The better we understand this process, the better we can protect human health and create technologies that are inspired by nature’s intelligence, explains Priyanka Mehra.
Priyanka’s work shows that evolution is not a fixed process but rather a dynamic one, where genetic interactions constantly adjust to face new challenges. These insights could guide future breakthroughs, from improving medical treatments to shaping the next generation of adaptive artificial life systems.
Read the full doctoral thesis: Epistasis, Pleiotropy, Robustness, and Evolvability: Insights into Evolutionary Dynamics