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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
UPLC-ELSD Analysis of Algal Lipid Classes and Derivatization of Bound and Free Fatty Acids and Sterols for GC-MS Methods
|
|---|---|
| Chapter number | 109 |
| Book title |
Biofuels from Algae
|
| Published in |
Methods in molecular biology, November 2017
|
| DOI | 10.1007/7651_2017_109 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-9415-1, 978-1-4939-9416-8
|
| Authors |
Tuulikki Seppänen-Laakso, Heli Nygren, Heiko Rischer, Seppänen-Laakso, Tuulikki, Nygren, Heli, Rischer, Heiko |
| Abstract |
Constituents of microalgae and sample preparation for UPLC-ELSD and GC-MS analyses are described. Bound fatty acids from acylglycerols, alkylacylglycerols, galactosyldiacylglycerols, glycerophospholipids, and sterol esters are derivatized by using transesterification with sodium methoxide to form fatty acid methyl esters. Compounds containing free hydroxyl groups, either present originally or formed during previous step, like free fatty acids, sterols, α-tocopherol, phytol, and nonesterified alkoxyglycerols, are trimethylsilylated. The compounds in algal lipid extract are subsequently derivatized by these two steps. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 33% |
| Germany | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 27% |
| Researcher | 3 | 20% |
| Professor > Associate Professor | 2 | 13% |
| Student > Bachelor | 1 | 7% |
| Unknown | 5 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 33% |
| Chemistry | 3 | 20% |
| Chemical Engineering | 2 | 13% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 7% |
| Unknown | 4 | 27% |
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 30 December 2017.
All research outputs
#17,923,510
of 23,012,811 outputs
Outputs from Methods in molecular biology
#7,286
of 13,156 outputs
Outputs of similar age
#305,449
of 437,756 outputs
Outputs of similar age from Methods in molecular biology
#886
of 1,528 outputs
Altmetric has tracked 23,012,811 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,156 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.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 437,756 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,528 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.