Plant Metabolomics
Springer New York
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| Chapter title |
Semi-targeted Lipidomics of Plant Acyl Lipids Using UPLC-HR-MS in Combination with a Data-Independent Acquisition Mode
|
|---|---|
| Book title |
Plant Metabolomics
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7819-9_10 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7818-2, 978-1-4939-7819-9
|
| Authors |
Mohamed A. Salem, Patrick Giavalisco |
| Abstract |
In recent years, multiple mass-spectrometric methods have been developed to tackle fundamental analytical questions in the field of biology and biochemistry. One essential approach relies on the use of liquid chromatography (LC), for efficient compound separation, coupled to high-resolution mass spectrometry (HR-MS). Even though these techniques are highly sensitive allowing for the reliable measurement of several thousand mass features, the major bottleneck is to convert the measured masses into annotated lipid species. To overcome this problem, we present a simple, example-based workflow, which provides an introduction to basic strategies for the manual validation of LC-MS-based lipidomic data. The whole strategy makes use of a data-independent acquisition (DIA) method, where alternating MS measurement cycles using high and low-energy scans are used. This measurement strategy allows to reliably annotate lipids, based on the exact mass measurements of intact, but also fragmented lipids from continuously recorded spectra. |
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 % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 10 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 30% |
| Student > Master | 3 | 30% |
| Lecturer | 1 | 10% |
| Unknown | 3 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 20% |
| Biochemistry, Genetics and Molecular Biology | 2 | 20% |
| Agricultural and Biological Sciences | 2 | 20% |
| Chemistry | 1 | 10% |
| Unknown | 3 | 30% |
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 06 June 2018.
All research outputs
#17,953,455
of 23,054,359 outputs
Outputs from Methods in molecular biology
#7,311
of 13,196 outputs
Outputs of similar age
#310,501
of 442,464 outputs
Outputs of similar age from Methods in molecular biology
#869
of 1,499 outputs
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So far Altmetric has tracked 13,196 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 39th percentile – i.e., 39% 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 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.