Mass spectrometry-based metabolomics.

By Katja Dettmer, P. Aronov, Bruce D. Hammock. Mass spectrometry reviews (Print), 2007

2,103 citations recorded by the source corpus.

Subfields: Molecular Biology, Spectroscopy

View Paper: https://www.semanticscholar.org/paper/2174278c590704f3771237baabc897f97fd97283

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Citations in the corpus

Activation and regulation of primary metabolism during seed germination (2014, background): “…are coupled with the use of mapping populations, which enables us to elucidate the genetic basis of the regulatory mechanisms of germination (Koornneef et al., 2002; Fait et al., 2006; Dettmer et al., 2007; Catusse et al., 2008; Angelovici et al., 2009; Toubiana et al., 2012; Joosen et al., 2013).”
Genome-scale models of bacterial metabolism: reconstruction and applications (2008, background): “MS and nuclear magnetic resonance (NMR) techniques are able to identify and quantify large sets of metabolites at high throughput (Dunn et al ., 2005; Dettmer et al ., 2007).”
High-throughput tissue extraction protocol for NMR- and MS-based metabolomics. (2008, methodology): “both are capable of high sample throughput and automated analysis [14, 15 ].”
Machine Learning and Integrative Analysis of Biomedical Big Data (2019, background): “Mass spectrometry [4,5] allows us to efficiently identify and quantify proteins, metabolites and lipids in cells, capturing underlying cellular variations in response to physiological and pathological changes.”
Missing Value Imputation Approach for Mass Spectrometry-based Metabolomics Data (2018, methodology): “In contrast, these two determined value imputations performed stably on data with different proportions of missing values since the imputed “average” values made the mean squared error, the numerator of formula (1), equals/close to the denominator which is the variance of missing elements in complet”
xMSanalyzer: automated pipeline for improved feature detection and downstream analysis of large-scale, non-targeted metabolomics data (2013, background): “Applications include metabolite profiling of tumor samples [1], identifying disease biomarkers [2], and studying complex biological networks [3].”
Metabolomics for functional genomics, systems biology, and biotechnology. (2010, methodology): “Since there is no single technology currently available (or likely in the near future) to detect all compounds found in plants or any other organism (46, 75, 161), a combination of multiple analytical techniques, such as gas chromatography (GC), liquid chromatography (LC), capillary electrophoresis ”