Development of a robust and repeatable UPLC-MS method for the long-term metabolomic study of human serum.
By E. Zelená, Warwick B. Dunn, David Broadhurst, S. Francis-McIntyre, K. Carroll, P. Begley, S. O’Hagan, Joshua D. Knowles, A. Halsall, Ian A. Wilson and 1 more. Analytical Chemistry, 2009
715 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Molecular Biology, Spectroscopy
View Paper: https://www.semanticscholar.org/paper/bbd9384731874377121a9487089787d4bd5459f6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
In Molecular Biology
- David S. Wishart
- Jianguo Xia
- Jeremy K. Nicholson
- Igor Sinelnikov
- Warwick B. Dunn
- Royston Goodacre
- David Broadhurst
- Ian A. Wilson
In Spectroscopy
- David S. Wishart
- Jianguo Xia
- Igor Sinelnikov
- Royston Goodacre
- Ian A. Wilson
- David Broadhurst
- R. Mandal
- Jeremy K. Nicholson
Citations in the corpus
- Guidelines and considerations for the use of system suitability and quality control samples in mass spectrometry assays applied in untargeted clinical metabolomic studies (2018, background): “This conditioning process allows higher reproducibility data to be attained for the biological test samples by removing variability in retention times and stabilizing detector response (Zelena et al. 2009).”
- Global metabolic profiling procedures for urine using UPLC–MS (2010, background): “MS-based metabolite profiling In the context of metabolic profiling, MS, when carried out carefully, can afford sensitive, accurate and reproducible measurements of the metabolites present in biofluids, tissues or organisms, with the ability to cover a wide dynamic rang”
- The Human Serum Metabolome (2011, background): “In addition to these referential clinical chemistry studies, several groups have applied various ‘‘global’’ metabolomic or metabolite profiling methods, such as high resolution nuclear magnetic resonance (NMR) spectroscopy [28,29], high performance liquid chromatography (HPLC) [30], amino acid analy”
- NOREVA: normalization and evaluation of MS-based metabolomics data (2017, background): “Signal drift and batch effect are frequently encountered in metabolic profiling, especially the long-term and large-scale one whose time span is usually several months or even years (5,23).”