ArticleJournal of biomolecular NMR2017
Maximal clique method for the automated analysis of NMR TOCSY spectra of complex mixtures.
Article in Journal of biomolecular NMR, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Problems, principles and progress in computational annotation of NMR metabolomics data.Metabolomics : Official journal of the Metabolomic Society · 2022Review
- Database Independent Automated Structure Elucidation of Organic Molecules Based on IR,Journal of chemical information and modeling · 2021Article
- Quantitative NMR-Based Biomedical Metabolomics: Current Status and Applications.Molecules (Basel, Switzerland) · 2020Review
- Effect of Biochar on Microbial Growth: A Metabolomics and Bacteriological Investigation in E. coli.Environmental science & technology · 2019Article
- Identification of Unknown Metabolomics Mixture Compounds by Combining NMR, MS, and Cheminformatics.Methods in enzymology · 2019Article
- Non-Uniform and Absolute Minimal Sampling for High-Throughput Multidimensional NMR Applications.Chemistry (Weinheim an der Bergstrasse, Germany) · 2018Review
- The Omics Revolution Continues: The Maturation of High-Throughput Biological Data Sources.Yearbook of medical informatics · 2018Review
- Accurate Identification of Unknown and Known Metabolic Mixture Components by Combining 3D NMR with Fourier Transform Ion Cyclotron Resonance Tandem Mass Spectrometry.Journal of proteome research · 2017Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Characterization of the chemical components of complex mixtures in solution is important in many areas of biochemistry and chemical biology, including metabolomics. The use of 2D NMR total correlation spectroscopy (TOCSY) experiments has proven very useful for the identification of known metabolites as well as for the characterization of metabolites that are unknown by taking advantage of the good resolution and high sensitivity of this homonuclear experiment. Due to the complexity of the resulting spectra, automation is critical to facilitate and speed-up their analysis and enable high-throughput applications. To better meet these emerging needs, an automated spin-system identification algorithm of TOCSY spectra is introduced that represents the cross-peaks and their connectivities as a mathematical graph, for which all subgraphs are determined that are maximal cliques. Each maximal clique can be assigned to an individual spin system thereby providing a robust deconvolution of the original spectrum for the easy extraction of critical spin system information. The approach is demonstrated for a complex metabolite mixture consisting of 20 compounds and for E. coli cell lysate.
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Registered trials
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