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Deciphering complex metabolite mixtures by unsupervised and supervised substructure discovery and semi-automated annotation from MS/MS spectra
View ORCID ProfileSimon Rogers, Cher Wei Ong, View ORCID ProfileJoe Wandy, View ORCID ProfileMadeleine Ernst, View ORCID ProfileLars Ridder, View ORCID ProfileJustin J.J. van der Hooft
doi: https://doi.org/10.1101/491506
Simon Rogers
1School of Computing Science, University of Glasgow, Glasgow, UK
Cher Wei Ong
1School of Computing Science, University of Glasgow, Glasgow, UK
Joe Wandy
2Glasgow Polyomics, University of Glasgow, Glasgow, UK
Madeleine Ernst
3Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA.
4Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, San Diego, California, USA
Lars Ridder
5Netherlands eScience Center, Amsterdam, The Netherlands
Justin J.J. van der Hooft
6Bioinformatics Group, Wageningen University, Wageningen, The Netherlands
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Posted December 12, 2018.
Deciphering complex metabolite mixtures by unsupervised and supervised substructure discovery and semi-automated annotation from MS/MS spectra
Simon Rogers, Cher Wei Ong, Joe Wandy, Madeleine Ernst, Lars Ridder, Justin J.J. van der Hooft
bioRxiv 491506; doi: https://doi.org/10.1101/491506
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