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

ABSTRACT: 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 spectrometry fragmentation data. Moreover, in silico annotation tools obtain and rank candidate molecules for fragmentation spectra. Ideally, all structural information obtained and inferred from these computational tools could be combined to increase the resulting chemical insight one can obtain from a data set. However, integration is currently hampered as each tool has its own output format and efficient matching of data across these tools is lacking. Here, we introduce MolNetEnhancer, a workflow tha

SUBMITTER: Ernst M 

PROVIDER: S-EPMC6680503 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature