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Auto-deconvolution and molecular networking of gas chromatography-mass spectrometry data.

NCJ Number
303983
Journal
Nature Biotechnology Volume: 39 Issue: 2 Dated: 2021
Author(s)
Alexander A. Aksenov; Ivan Laponogov; Zheng Zhang; Sophie L. F. Doran; Ilaria Belluomo; et al
Date Published
2021
Annotation

The current project engineered a machine-learning approach, MSHub, to enable auto-deconvolution of gas chromatography–mass spectrometry (GC–MS) data.

 

Abstract

It then designed workflows to enable the community to store, process, share, annotate, compare, and perform molecular networking of GC–MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples. (publisher abstract modified)

Date Published: January 1, 2021