Application of LLMs/Transformer-Based Models for Metabolite Annotation in Metabolomics

Abstract

This review examines how large language models and Transformer-based methods can support metabolite annotation in LC-MS metabolomics, including molecular structure annotation, retention time prediction, and mass-spectra generation. It also discusses opportunities for integrating metabolomics with other molecular data.

Qiao Liu

Assistant Professor of Biostatistics

My research interests include generative AI, high-dimensional data analysis, and computational biology.