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Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry

Overview of attention for article published in BMC Bioinformatics, March 2007
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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 (89th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
2 tweeters
patent
1 patent
q&a
1 Q&A thread

Citations

dimensions_citation
886 Dimensions

Readers on

mendeley
1054 Mendeley
citeulike
4 CiteULike
connotea
2 Connotea
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Title
Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry
Published in
BMC Bioinformatics, March 2007
DOI 10.1186/1471-2105-8-105
Pubmed ID
Authors

Tobias Kind, Oliver Fiehn

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 1,054 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 11 1%
United Kingdom 6 <1%
Netherlands 5 <1%
Switzerland 4 <1%
Germany 4 <1%
Denmark 4 <1%
Spain 3 <1%
India 3 <1%
Sweden 3 <1%
Other 18 2%
Unknown 993 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 296 28%
Researcher 209 20%
Student > Master 118 11%
Student > Doctoral Student 73 7%
Student > Bachelor 73 7%
Other 155 15%
Unknown 130 12%
Readers by discipline Count As %
Chemistry 330 31%
Agricultural and Biological Sciences 197 19%
Biochemistry, Genetics and Molecular Biology 119 11%
Environmental Science 66 6%
Engineering 38 4%
Other 121 11%
Unknown 183 17%

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 13 January 2021.
All research outputs
#1,308,456
of 20,995,223 outputs
Outputs from BMC Bioinformatics
#254
of 6,857 outputs
Outputs of similar age
#34,550
of 328,045 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 38 outputs
Altmetric has tracked 20,995,223 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 6,857 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. 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 328,045 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 38 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 99% of its contemporaries.