Deciphering complex metabolite mixtures by unsupervised and supervised substructure discovery and semi-automated annotation from MS/MS spectra

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Summary

This work describes how additional strategies, taking advantage of combinatorial in-silico matching of experimental mass features to substructures of candidate molecules, can facilitate semi-automated annotation of substructURES, and shows how this approach accelerates the Mass2Motif annotation process and therefore broadens the chemical space spanned by characterized motifs.

Type
article
Published
2018-12-09
Cited by
51
References
40
Access
Open access

Keywords

Substructure, Annotation, Metabolite, Computer science, Computational biology

References

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