Liquid-chromatography retention order prediction for metabolite identification
Author:
Affiliation:
1. Department of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Espoo, Finland
2. Department for Computer Science, Chair for Bioinformatics, Friedrich-Schiller-University, Jena, Germany
Funder
Academy of Finland
MIDAS
Aalto Science-IT infrastructure
Publisher
Oxford University Press (OUP)
Subject
Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability
Link
http://academic.oup.com/bioinformatics/article-pdf/34/17/i875/25702364/bty590.pdf
Reference33 articles.
1. Retention time prediction improves identification in nontargeted lipidomics approaches;Aicheler;Anal. Chem.,2015
2. Global chemical analysis of biology by mass spectrometry;Aksenov;Nat. Rev. Chem.,2017
3. CFM-ID: a web server for annotation, spectrum prediction and metabolite identification from tandem mass spectra;Allen;Nucleic Acids Res.,2014
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