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X Demographics
Mendeley readers
Attention Score in Context
| Title |
CheNER: a tool for the identification of chemical entities and their classes in biomedical literature
|
|---|---|
| Published in |
Journal of Cheminformatics, January 2015
|
| DOI | 10.1186/1758-2946-7-s1-s15 |
| Pubmed ID | |
| Authors |
Anabel Usié, Joaquim Cruz, Jorge Comas, Francesc Solsona, Rui Alves |
| Abstract |
Small chemical molecules regulate biological processes at the molecular level. Those molecules are often involved in causing or treating pathological states. Automatically identifying such molecules in biomedical text is difficult due to both, the diverse morphology of chemical names and the alternative types of nomenclature that are simultaneously used to describe them. To address these issues, the last BioCreAtIvE challenge proposed a CHEMDNER task, which is a Named Entity Recognition (NER) challenge that aims at labelling different types of chemical names in biomedical text. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 5% |
| Portugal | 1 | 3% |
| United States | 1 | 3% |
| Unknown | 33 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 24% |
| Researcher | 9 | 24% |
| Professor > Associate Professor | 3 | 8% |
| Student > Doctoral Student | 2 | 5% |
| Student > Bachelor | 2 | 5% |
| Other | 8 | 22% |
| Unknown | 4 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 12 | 32% |
| Agricultural and Biological Sciences | 5 | 14% |
| Biochemistry, Genetics and Molecular Biology | 3 | 8% |
| Chemistry | 2 | 5% |
| Environmental Science | 1 | 3% |
| Other | 7 | 19% |
| Unknown | 7 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 27 March 2015.
All research outputs
#18,836,331
of 23,344,526 outputs
Outputs from Journal of Cheminformatics
#829
of 862 outputs
Outputs of similar age
#259,422
of 355,201 outputs
Outputs of similar age from Journal of Cheminformatics
#16
of 18 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 862 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one is in the 1st percentile – i.e., 1% 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 355,201 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.