Department of Chemistry Seminar - Integrating High-Resolution Mass Spectrometry and Machine Learning to Explore Chemical Complexity in Exposomics

Speaker: Prof. Tao HUAN

Institution: Department of Chemistry, The University of British Columbia, Vancouver, Canada

Hosted by: Prof. Jianzhen YU

Abstract

The human exposome encompasses an extraordinarily diverse chemical space, much of which remains poorly characterized by conventional analytical approaches. In this seminar, I will highlight research efforts from the Huan Lab aimed at integrating high-resolution mass spectrometry and machine learning to better interrogate this chemical complexity. First, I will introduce the concept of the “long-tail exposome,” emphasizing the analytical challenges associated with the large number of low-abundance and infrequently detected environmental chemicals. The talk will then present machine learning-guided strategies for recognizing halogen-containing compounds, an important class of environmental contaminants with distinctive yet often underutilized mass spectrometric signatures. Finally, I will discuss chemistry-informed spectral similarity approaches that incorporate chemical knowledge into MS/MS comparison to improve the characterization of structurally related known and unknown compounds. Together, these examples demonstrate how the integration of high-resolution mass spectrometry, computational approaches, and machine learning can expand chemical coverage and improve molecular characterization in exposomics.