↓ Skip to main content

Highly sensitive feature detection for high resolution LC/MS

Overview of attention for article published in BMC Bioinformatics, November 2008
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
1 news outlet
twitter
18 X users
patent
3 patents

Citations

dimensions_citation
919 Dimensions

Readers on

mendeley
860 Mendeley
citeulike
7 CiteULike
Title
Highly sensitive feature detection for high resolution LC/MS
Published in
BMC Bioinformatics, November 2008
DOI 10.1186/1471-2105-9-504
Pubmed ID
Authors

Ralf Tautenhahn, Christoph Böttcher, Steffen Neumann

X Demographics

X Demographics

The data shown below were collected from the profiles of 18 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 860 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 8 <1%
Germany 5 <1%
United States 4 <1%
South Africa 4 <1%
Brazil 3 <1%
Austria 3 <1%
Portugal 2 <1%
Belgium 2 <1%
Italy 2 <1%
Other 7 <1%
Unknown 820 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 233 27%
Researcher 186 22%
Student > Master 96 11%
Student > Bachelor 80 9%
Student > Doctoral Student 45 5%
Other 102 12%
Unknown 118 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 204 24%
Chemistry 182 21%
Biochemistry, Genetics and Molecular Biology 105 12%
Computer Science 35 4%
Environmental Science 33 4%
Other 138 16%
Unknown 163 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 21 January 2021.
All research outputs
#1,348,711
of 24,903,209 outputs
Outputs from BMC Bioinformatics
#171
of 7,606 outputs
Outputs of similar age
#5,014
of 179,469 outputs
Outputs of similar age from BMC Bioinformatics
#3
of 47 outputs
Altmetric has tracked 24,903,209 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,606 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 97% 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 179,469 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 97% of its contemporaries.
We're also able to compare this research output to 47 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.