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Building blocks for automated elucidation of metabolites: Machine learning methods for NMR prediction

Overview of attention for article published in BMC Bioinformatics, September 2008
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Mentioned by

patent
1 patent

Readers on

mendeley
142 Mendeley
citeulike
2 CiteULike
connotea
1 Connotea
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Title
Building blocks for automated elucidation of metabolites: Machine learning methods for NMR prediction
Published in
BMC Bioinformatics, September 2008
DOI 10.1186/1471-2105-9-400
Pubmed ID
Authors

Stefan Kuhn, Björn Egert, Steffen Neumann, Christoph Steinbeck

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 142 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 2 1%
Germany 2 1%
Brazil 2 1%
Netherlands 1 <1%
Sweden 1 <1%
United Kingdom 1 <1%
Russia 1 <1%
United States 1 <1%
Unknown 131 92%

Demographic breakdown

Readers by professional status Count As %
Student > Master 27 19%
Student > Ph. D. Student 25 18%
Researcher 21 15%
Student > Bachelor 14 10%
Student > Doctoral Student 6 4%
Other 17 12%
Unknown 32 23%
Readers by discipline Count As %
Chemistry 33 23%
Agricultural and Biological Sciences 23 16%
Computer Science 14 10%
Environmental Science 10 7%
Engineering 6 4%
Other 23 16%
Unknown 33 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 28 May 2020.
All research outputs
#7,645,563
of 23,278,709 outputs
Outputs from BMC Bioinformatics
#3,070
of 7,369 outputs
Outputs of similar age
#32,032
of 88,781 outputs
Outputs of similar age from BMC Bioinformatics
#14
of 36 outputs
Altmetric has tracked 23,278,709 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,369 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 gotten more attention than average, scoring higher than 50% 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 88,781 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.