Scientists at Tel Aviv University (TAU) have developed a new AI tool that helps understand how cells react to cancer treatments. This tool, called scNET, combines two types of biological data: gene activity at the single-cell level and known gene interactions.
The researchers say this approach helps detect small but important changes in cells, especially when they are exposed to treatments like chemotherapy or immunotherapy. The study, published in Nature Methods, was led by PhD student Ron Sheinin under the supervision of Professors Asaf Madi and Roded Sharan.
How Does scNET Work?
scNET uses AI to analyze gene expression data alongside a “biological social network”—a map of how genes interact. This method helps uncover hidden gene activity patterns. For example, the researchers found that T cells, which attack cancer cells, become more active after treatment.
“This AI tool lets us see things that were hard to detect before,” said Prof. Sharan. “It can help researchers find new answers in cancer research and medicine.”
Future Applications
Beyond cancer treatment, scNET could help in developing new therapies, understanding the immune system, and personalizing medicine.
“This is just the beginning,” said Sheinin. “Our AI framework can be used to study many diseases and guide medical decisions based on how cells respond to treatment.”
Source: jpost
