MolNetEnhancer: Enhanced Molecular Networks by Integrating Metabolome Mining and Annotation Tools

MolNetEnhancer: Enhanced Molecular Networks by Integrating Metabolome Mining and Annotation Tools

Metabolomics has started to embrace computational approaches for chemical interpretation of large data sets. Yet, metabolite annotation remains a key challenge. Recently, molecular networking and MS2LDA emerged as molecular mining tools that find molecular families and substructures in mass spectrom...

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Bibliographic Details
Main Authors: Madeleine Ernst, Kyo Bin Kang, Andrés Mauricio Caraballo-Rodríguez, Louis-Felix Nothias, Joe Wandy, Christopher Chen, Mingxun Wang, Simon Rogers, Marnix H. Medema, Pieter C. Dorrestein, Justin J.J. van der Hooft
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Metabolites
Subjects:
chemical classification
in silico workflows
metabolite annotation
metabolite identification
metabolome mining
molecular families
networking
substructures
Online Access:https://www.mdpi.com/2218-1989/9/7/144

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https://www.mdpi.com/2218-1989/9/7/144

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