Chapter title |
HILIC-MS/MS Multi-Targeted Method for Metabolomics Applications
|
---|---|
Chapter number | 5 |
Book title |
Metabolic Profiling
|
Published in |
Methods in molecular biology, April 2018
|
DOI | 10.1007/978-1-4939-7643-0_5 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7642-3, 978-1-4939-7643-0
|
Authors |
Christina Virgiliou, Helen G. Gika, Georgios A. Theodoridis, Virgiliou, Christina, Gika, Helen G., Theodoridis, Georgios A. |
Abstract |
Metabolomics aims at the identification and quantification of key-end point metabolites, basically polar, in order to study changes in biochemical activities in response to pathophysiological stimuli or genetic modifications. Targeted profiling assays have enjoyed a growing popularity during the last years with LC-MS/MS as a powerful tool for development of such (semi-) quantitative methods for a large number of metabolites. Here we describe a method for absolute quantification of ca. 100 metabolites belonging to key metabolite classes such as sugars, amino acids, nucleotides, organic acids, and amines with a hydrophilic interaction liquid chromatography (HILIC) system comprised of ultra (high) performance liquid chromatography (UHPLC) with detection on a triple-quadrupole mass spectrometer operating in both positive and negative electrospray ionization modes. |
X Demographics
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Germany | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 22 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 5 | 23% |
Student > Bachelor | 3 | 14% |
Researcher | 2 | 9% |
Student > Master | 2 | 9% |
Professor | 1 | 5% |
Other | 3 | 14% |
Unknown | 6 | 27% |
Readers by discipline | Count | As % |
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Chemistry | 5 | 23% |
Agricultural and Biological Sciences | 4 | 18% |
Pharmacology, Toxicology and Pharmaceutical Science | 3 | 14% |
Biochemistry, Genetics and Molecular Biology | 3 | 14% |
Medicine and Dentistry | 1 | 5% |
Other | 1 | 5% |
Unknown | 5 | 23% |