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Mendeley readers
Attention Score in Context
| Title |
Facilitating the development of controlled vocabularies for metabolomics technologies with text mining
|
|---|---|
| Published in |
BMC Bioinformatics, April 2008
|
| DOI | 10.1186/1471-2105-9-s5-s5 |
| Pubmed ID | |
| Authors |
Irena Spasić, Daniel Schober, Susanna-Assunta Sansone, Dietrich Rebholz-Schuhmann, Douglas B Kell, Norman W Paton |
| Abstract |
Many bioinformatics applications rely on controlled vocabularies or ontologies to consistently interpret and seamlessly integrate information scattered across public resources. Experimental data sets from metabolomics studies need to be integrated with one another, but also with data produced by other types of omics studies in the spirit of systems biology, hence the pressing need for vocabularies and ontologies in metabolomics. However, it is time-consuming and non trivial to construct these resources manually. |
Mendeley readers
The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 3% |
| United States | 2 | 3% |
| Brazil | 1 | 1% |
| Spain | 1 | 1% |
| Malaysia | 1 | 1% |
| Unknown | 63 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 17 | 24% |
| Student > Ph. D. Student | 6 | 9% |
| Student > Master | 6 | 9% |
| Other | 5 | 7% |
| Student > Bachelor | 5 | 7% |
| Other | 21 | 30% |
| Unknown | 10 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 19 | 27% |
| Agricultural and Biological Sciences | 14 | 20% |
| Medicine and Dentistry | 8 | 11% |
| Environmental Science | 4 | 6% |
| Linguistics | 3 | 4% |
| Other | 12 | 17% |
| Unknown | 10 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 16 February 2009.
All research outputs
#5,576,537
of 22,705,019 outputs
Outputs from BMC Bioinformatics
#2,044
of 7,255 outputs
Outputs of similar age
#22,275
of 79,431 outputs
Outputs of similar age from BMC Bioinformatics
#12
of 53 outputs
Altmetric has tracked 22,705,019 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,255 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 71% 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 79,431 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 53 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.