Identifying New Toxins using Machine Learning

15 August, 2024
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A new study by Dr. Asaf Levy, Aleks Danov, and Inbal Pollin together with Dr. Phillipos Papathanos of the Robert H. Smith Faculty of Agriculture, Food and Environment and Prof. Tommy Kaplan of the Rachel and Selim Benin School of Computer Science and Engineering, offers insights into a bacterial weapons system functioning as a microscopic needle.

The researchers developed a machine learning tool to identify toxins, with potential applications in medicine, agriculture, and biotechnology, including new antibiotics.

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