AI-based search engine can help researchers find new chemical reactions in data archives

In a joint project between the Zelinsky Institute of Organic Chemistry and Skoltech, a research group led by RAS Academician Valentin Ananikov has developed a unique machine-learning-based search engine for analyzing vast amounts of high-resolution mass spectrometry data. Machine learning allows exploring terabytes of accumulated data without new experiments. The algorithm accelerates the search for new compounds, reduces costs, and makes research more environmentally friendly.