IIITH Researchers Use Math To Explain Hidden Patterns In Living Systems
Researchers are using reaction networks and dynamical systems to study these hidden patterns in living systems: Reports
HYDERABAD: Scientists use mathematical models to explain why mosquito populations surge after rain, how species disappear without warning or why ecosystems recover when a missing element is restored. At IIITH, researchers are using reaction networks and dynamical systems to study these hidden patterns in living systems.
Prof. Abhishek Deshpande from the Center for Computational Natural Sciences and Bioinformatics said the reaction networks helped scientists understand chains of cause and effect. He pointed to the Yellowstone example in the United States, where wolves were reintroduced about 30 years ago after their numbers had collapsed. Elk populations had risen sharply in their absence, damaging young trees and riverbanks.
Prof. Deshpande explained, “When wolves returned, the balance shifted again. It showed how one species can influence everything around it. Reaction networks help us explain why such changes unfold the way they do.”
One stream of his recent work focuses on dynamical systems. A study coauthored with researchers Samay Kothari and Jiaxin Jin and published in the ‘SIAM Journal on Applied Dynamical Systems’ demonstrated how the behaviour of one family of reaction networks can be embedded within another.
The work drew from biochemical interactions such as the oxidation of uric acid in the presence of uricase. Another study with Kothari, published in the ‘Journal of Mathematical Chemistry’, examined endotactic networks and their ability to hold infinitely many steady states.
IIITH researchers are also exploring how chemical interactions can behave like computing systems. Prof. Deshpande said this approach allows scientists to test new ways of implementing algorithms.
He said, “Using chemistry to perform computation is an active direction. Reaction networks can reproduce the behaviour of Support Vector Machines and encourage us to rethink how computation itself can be represented.” This work was coauthored with MS by Research student Amey Choudhary and Jiaxin Jin. Choudhary’s extended study of the idea earned him the IndiaAI fellowship, which supports students working on projects with both theoretical and practical relevance.
Another research thread looks at origin of life models through autocatalytic interactions. Findings published in ‘Mathematical Biosciences’ analysed how self-reinforcing molecular networks might persist over time. The group has also examined homeostasis, the ability of organisms to maintain stable internal conditions. Their work in the ‘Journal of Mathematical Biology’ explains how the structure of a network can determine whether homeostasis is possible.
Prof. Deshpande said mathematical biology helps scientists uncover the rules that guide living systems. He said, “These tools let us ask why life behaves the way it does and how we can apply that understanding to medicine, conservation and technology.”
