Topic overview

Start with the big picture

Metabolomics can be untargeted, surveying metabolites without prior selection, or targeted, monitoring predefined markers for purposes such as herbal-drug quality control. Techniques including NMR, LC-HRMS, and GC-MS help characterize chemical profiles, while molecular networking and computational annotation assist with recognizing and predicting compounds. Genomic approaches identify biosynthetic gene clusters and can be paired with functional validation to investigate their role in natural-product production. Integrating genomic and metabolomic data can connect genes with chemotypes and help prioritize candidates for discovery. The broader field also uses bioactivity correlations, RNA-seq, GWAS, and supporting databases to investigate regulation, useful traits, and chemical diversity. These methods offer powerful tools, while raising practical challenges in interpretation and standardization.