Molecular networking has become a key method to visualize and annotate the chemical space in non-targeted mass spectrometry data. We present feature-based molecular networking (FBMN) as an analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure that builds on chromatographic feature detection and alignment tools. FBMN enables quantitative analysis and resolution of isomers, including from ion mobility spectrometry. Feature-based molecular networking allows the generation of molecular networks for mass spectrometry data that can recognize isomers, incorporate relative quantification and integrate ion mobility data.

Feature-based molecular networking in the GNPS analysis environment