Feature-based molecular networking in the GNPS analysis environment.
Louis-Félix NothiasDaniel PetrasRobin SchmidKai DührkopJohannes RainerAbinesh SarvepalliIvan ProtsyukMadeleine ErnstHiroshi TsugawaMarkus FleischauerFabian AichelerAlexander A AksenovOliver AlkaPierre-Marie AllardAiko BarschXavier CachetAndrés Mauricio Caraballo-RodriguezRicardo R Da SilvaTam DangNeha GargJulia M GauglitzAlexey GurevichGiorgis IsaacAlan K JarmuschZdeněk KameníkKyo-Bin KangNikolas KesslerIrina KoesterAnsgar KorfAudrey Le GouëllecMarcus LudwigChristian Martin HLaura-Isobel McCallJonathan McSaylesSven W MeyerHosein MohimaniMustafa MorsyOriane MoyneSteffen NeumannHeiko NeuwegerNgoc Hung NguyenMelissa Nothias-EspositoJulien PaoliniVanessa V PhelanTomáš PluskalRobert A QuinnSimon RogersBindesh ShresthaAnupriya TripathiJustin Johan Jozias van der HooftFernando VargasKelly C WeldonMichael WittingHeejung YangZheng ZhangFlorian ZubeilOliver KohlbacherSebastian BöckerTheodore AlexandrovNuno BandeiraMingxun WangPieter C DorresteinPublished in: Nature methods (2020)
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.