Plant Metabolomics
Springer New York
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Attention Score in Context
| Chapter title |
Quantification of Sugars and Organic Acids in Biological Matrices Using GC-QqQ-MS
|
|---|---|
| Chapter number | 15 |
| Book title |
Plant Metabolomics
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7819-9_15 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7818-2, 978-1-4939-7819-9
|
| Authors |
Nirupama Samanmalie Jayasinghe, Himasha Mendis, Ute Roessner, Daniel Anthony Dias, Jayasinghe, Nirupama Samanmalie, Mendis, Himasha, Roessner, Ute, Dias, Daniel Anthony |
| Abstract |
Gas chromatography coupled with triple quadrupole mass spectrometry (GC-QqQ-MS) can be used to accurately quantify endogenous small molecules extracted from biological samples such as plants and human fluids including sera and urine. In order to quantify primary metabolites typically from central carbon metabolism such as sugars from glycolysis and the pentose phosphate pathway; and organic acids involved in the tricarboxylic acid (TCA) cycle; polar endogenous metabolites must be extracted from the samples of interest, chemically derivatized and quantified against a linear calibration curve to a corresponding authentic standard. This chapter describes how to quantify a combination of 48 primary metabolites belonging to classes of sugars, sugar alcohols, sugar acids, sugar phosphates, and organic acids using a robust, optimized, multiple reaction monitoring (MRM)-based GC-QqQ-MS method. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 50% |
| Comoros | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 16 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 25% |
| Researcher | 4 | 25% |
| Student > Doctoral Student | 2 | 13% |
| Professor | 1 | 6% |
| Professor > Associate Professor | 1 | 6% |
| Other | 2 | 13% |
| Unknown | 2 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 38% |
| Biochemistry, Genetics and Molecular Biology | 3 | 19% |
| Business, Management and Accounting | 1 | 6% |
| Medicine and Dentistry | 1 | 6% |
| Chemistry | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 4 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 February 2019.
All research outputs
#15,536,861
of 23,090,520 outputs
Outputs from Methods in molecular biology
#5,410
of 13,206 outputs
Outputs of similar age
#270,129
of 442,634 outputs
Outputs of similar age from Methods in molecular biology
#596
of 1,499 outputs
Altmetric has tracked 23,090,520 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,206 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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We're also able to compare this research output to 1,499 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.