A team of scientists in Israel has created an artificial intelligence tool called scNET that could reshape how researchers study cell behavior and drug response. Tel Aviv University announced Tuesday that the new tool is designed to analyze single-cell gene activity with greater precision by filtering out the background noise that typically hampers current sequencing technologies.
The breakthrough was published in the journal Nature Methods. According to the university, scNET enhances the accuracy of genetic data analysis by integrating single-cell sequencing information with gene interaction networks—essentially mapping how genes influence one another. This approach allows researchers to uncover subtle biological responses that were previously obscured.
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In one set of trials, the researchers used scNET to study T cells, a key component of the immune system known for attacking tumors. The tool revealed how certain cancer treatments improved the T cells’ tumor-killing functions—an effect that had gone unnoticed using traditional methods.
“This is a clear demonstration of how artificial intelligence can cut through biological complexity,” the university said in its statement. The team behind the tool believes it could accelerate drug discovery and enable more personalized medical treatments by providing a clearer understanding of how cells react in different environments.
Tel Aviv University’s researchers said AI tools like scNET represent a major step toward decoding cell behavior and tailoring therapies to individual patients’ needs.