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X Demographics
Mendeley readers
Attention Score in Context
| Title |
On InChI and evaluating the quality of cross-reference links
|
|---|---|
| Published in |
Journal of Cheminformatics, April 2014
|
| DOI | 10.1186/1758-2946-6-15 |
| Pubmed ID | |
| Authors |
Jakub Galgonek, Jiří Vondrášek |
| Abstract |
There are many databases of small molecules focused on different aspects of research and its applications. Some tasks may require integration of information from various databases. However, determining which entries from different databases represent the same compound is not straightforward. Integration can be based, for example, on automatically generated cross-reference links between entries. Another approach is to use the manually curated links stored directly in databases. This study employs well-established InChI identifiers to measure the consistency and completeness of the manually curated links by comparing them with the automatically generated ones. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 33% |
| Germany | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 2 | 10% |
| Germany | 2 | 10% |
| Czechia | 1 | 5% |
| Unknown | 15 | 75% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 50% |
| Student > Ph. D. Student | 7 | 35% |
| Student > Bachelor | 1 | 5% |
| Student > Master | 1 | 5% |
| Other | 1 | 5% |
| Other | 0 | 0% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 6 | 30% |
| Chemistry | 5 | 25% |
| Biochemistry, Genetics and Molecular Biology | 3 | 15% |
| Agricultural and Biological Sciences | 2 | 10% |
| Engineering | 2 | 10% |
| Other | 2 | 10% |
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 April 2014.
All research outputs
#13,996,860
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#685
of 891 outputs
Outputs of similar age
#111,508
of 230,281 outputs
Outputs of similar age from Journal of Cheminformatics
#13
of 27 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 891 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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 230,281 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 51% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.