Comparison of computational approaches for identification and quantification of urinary metabolites in 1H NMR spectra-Reference-Cited by-同舟云学术

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Comparison of computational approaches for identification and quantification of urinary metabolites in 1H NMR spectra

Published:2018 Issue:18 Volume:10 Page:2129-2137
ISSN:1759-9660
Container-title:Analytical Methods
language:en
Short-container-title:Anal. Methods

Author:

Cassiède Marc¹²³⁴^ORCID,Mercier Pascal⁵²³⁴,Shipley Paul R.⁶⁷⁸⁴^ORCID,Dueck Meghan¹²³⁴,Kamravaei Samineh¹²³⁴,Nair Sindhu¹²³⁴,Mino James¹²³⁴,Pei Lei¹²³⁴,Broadhurst David⁹¹⁰¹¹¹²,Lacy Paige¹²³⁴^ORCID,Quémerais Bernadette¹²³⁴^ORCID

Affiliation:

1. Department of Medicine

2. University of Alberta

3. Edmonton

4. Canada

5. National High Field NMR Centre (NANUC)

6. Department of Chemistry

7. University of British Columbia

8. Kelowna

9. School of Science

10. Edith Cowan University

11. Perth

12. Australia

Abstract

A Monte Carlo simulation technique is used to accurately measure metabolite concentrations in urine.

Publisher

Royal Society of Chemistry (RSC)

Subject

General Engineering,General Chemical Engineering,Analytical Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2018/AY/C8AY00830B

Reference39 articles.

1. 'Metabonomics': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data

2. The association of fecal microbiota and fecal, blood serum and urine metabolites in myalgic encephalomyelitis/chronic fatigue syndrome

3. Assessment of 1 H NMR-based metabolomics analysis for normalization of urinary metals against creatinine

4. Automatic Data Reduction and Pattern Recognition Methods for Analysis of 1H Nuclear Magnetic Resonance Spectra of Human Urine from Normal and Pathological States

5. 750 MHz 1H NMR spectroscopy characterisation of the complex metabolic pattern of urine from patients with inborn errors of metabolism: 2-hydroxyglutaric aciduria and maple syrup urine disease

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3. Quantitative NMR-Based Biomedical Metabolomics: Current Status and Applications;Molecules;2020-11-04

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