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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Introducing glycomics data into the Semantic Web
|
|---|---|
| Published in |
Journal of Biomedical Semantics, November 2013
|
| DOI | 10.1186/2041-1480-4-39 |
| Pubmed ID | |
| Authors |
Kiyoko F Aoki-Kinoshita, Jerven Bolleman, Matthew P Campbell, Shin Kawano, Jin-Dong Kim, Thomas Lütteke, Masaaki Matsubara, Shujiro Okuda, Rene Ranzinger, Hiromichi Sawaki, Toshihide Shikanai, Daisuke Shinmachi, Yoshinori Suzuki, Philip Toukach, Issaku Yamada, Nicolle H Packer, Hisashi Narimatsu |
| Abstract |
Glycoscience is a research field focusing on complex carbohydrates (otherwise known as glycans)a, which can, for example, serve as "switches" that toggle between different functions of a glycoprotein or glycolipid. Due to the advancement of glycomics technologies that are used to characterize glycan structures, many glycomics databases are now publicly available and provide useful information for glycoscience research. However, these databases have almost no link to other life science databases. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Ghana | 1 | 17% |
| United Kingdom | 1 | 17% |
| Australia | 1 | 17% |
| Switzerland | 1 | 17% |
| Unknown | 2 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 2 | 4% |
| Netherlands | 2 | 4% |
| Mexico | 1 | 2% |
| Brazil | 1 | 2% |
| Unknown | 41 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 26% |
| Student > Master | 7 | 15% |
| Student > Ph. D. Student | 6 | 13% |
| Other | 5 | 11% |
| Student > Bachelor | 4 | 9% |
| Other | 11 | 23% |
| Unknown | 2 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 16 | 34% |
| Computer Science | 11 | 23% |
| Biochemistry, Genetics and Molecular Biology | 5 | 11% |
| Engineering | 4 | 9% |
| Chemistry | 3 | 6% |
| Other | 6 | 13% |
| Unknown | 2 | 4% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 2017.
All research outputs
#4,045,883
of 22,733,113 outputs
Outputs from Journal of Biomedical Semantics
#63
of 364 outputs
Outputs of similar age
#48,361
of 306,357 outputs
Outputs of similar age from Journal of Biomedical Semantics
#5
of 29 outputs
Altmetric has tracked 22,733,113 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 364 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done well, scoring higher than 82% 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 306,357 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 84% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.