| Title |
Filtering procedures for untargeted LC-MS metabolomics data
|
|---|---|
| Published in |
BMC Bioinformatics, June 2019
|
| DOI | 10.1186/s12859-019-2871-9 |
| Pubmed ID | |
| Authors |
Courtney Schiffman, Lauren Petrick, Kelsi Perttula, Yukiko Yano, Henrik Carlsson, Todd Whitehead, Catherine Metayer, Josie Hayes, Stephen Rappaport, Sandrine Dudoit |
X Demographics
The data shown below were collected from the profiles of 23 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 13% |
| United States | 3 | 13% |
| Sweden | 2 | 9% |
| India | 2 | 9% |
| France | 1 | 4% |
| Netherlands | 1 | 4% |
| Spain | 1 | 4% |
| Mexico | 1 | 4% |
| Korea, Republic of | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 7 | 30% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 15 | 65% |
| Members of the public | 7 | 30% |
| Science communicators (journalists, bloggers, editors) | 1 | 4% |
Mendeley readers
The data shown below were compiled from readership statistics for 253 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 253 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 62 | 25% |
| Student > Master | 37 | 15% |
| Researcher | 36 | 14% |
| Student > Bachelor | 23 | 9% |
| Student > Doctoral Student | 12 | 5% |
| Other | 27 | 11% |
| Unknown | 56 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 47 | 19% |
| Chemistry | 38 | 15% |
| Agricultural and Biological Sciences | 32 | 13% |
| Pharmacology, Toxicology and Pharmaceutical Science | 15 | 6% |
| Medicine and Dentistry | 11 | 4% |
| Other | 37 | 15% |
| Unknown | 73 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 22. 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 25 July 2023.
All research outputs
#1,679,866
of 25,205,261 outputs
Outputs from BMC Bioinformatics
#296
of 7,660 outputs
Outputs of similar age
#35,837
of 359,747 outputs
Outputs of similar age from BMC Bioinformatics
#10
of 185 outputs
Altmetric has tracked 25,205,261 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,660 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 96% of its peers.
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 359,747 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 185 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.