Metabolic Reaction Network-based Recursive Metabolite Identification for Untargeted Metabolomics

Abstract

Metabolite identification is a long-standing challenge in untargeted metabolomics and a major hurdle for functional metabolomics studies. Here, we developed a metabolic reaction network-based recursive algorithm and webserver called MetDNA for the large-scale and unambiguous identification of metabolites (available at http://metdna.zhulab.cn). We showcased the versatility of our workflow using different instrument platforms, data acquisition methods, and biological sample types and demonstrated that over 2,000 metabolites could be identified from one experiment.