Feature-based molecular networking in the GNPS analysis environment

Louis Félix Nothias, Daniel Petras, Robin Schmid, Kai Dührkop, Johannes Rainer, Abinesh Sarvepalli, Ivan Protsyuk, Madeleine Ernst, Hiroshi Tsugawa, Markus Fleischauer, Fabian Aicheler, Alexander A. Aksenov, Oliver Alka, Pierre Marie Allard, Aiko Barsch, Xavier Cachet, Andres Mauricio Caraballo-Rodriguez, Ricardo R. Da Silva, Tam Dang, Neha GargJulia M. Gauglitz, Alexey Gurevich, Giorgis Isaac, Alan K. Jarmusch, Zdeněk Kameník, Kyo Bin Kang, Nikolas Kessler, Irina Koester, Ansgar Korf, Audrey Le Gouellec, Marcus Ludwig, Christian Martin H, Laura Isobel McCall, Jonathan McSayles, Sven W. Meyer, Hosein Mohimani, Mustafa Morsy, Oriane Moyne, Steffen Neumann, Heiko Neuweger, Ngoc Hung Nguyen, Melissa Nothias-Esposito, Julien Paolini, Vanessa V. Phelan, Tomáš Pluskal, Robert A. Quinn, Simon Rogers, Bindesh Shrestha, Anupriya Tripathi, Justin J.J. van der Hooft, Fernando Vargas, Kelly C. Weldon, Michael Witting, Heejung Yang, Zheng Zhang, Florian Zubeil, Oliver Kohlbacher, Sebastian Böcker, Theodore Alexandrov, Nuno Bandeira, Mingxun Wang*, Pieter C. Dorrestein

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)905-908
Number of pages4
JournalNature Methods
Volume17
Issue number9
DOIs
Publication statusPublished - 24 Aug 2020

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