| Title |
Ranking relations between diseases, drugs and genes for a curation task
|
|---|---|
| Published in |
Journal of Biomedical Semantics, October 2012
|
| DOI | 10.1186/2041-1480-3-s3-s5 |
| Pubmed ID | |
| Authors |
Simon Clematide, Fabio Rinaldi |
| Abstract |
One of the key pieces of information which biomedical text mining systems are expected to extract from the literature are interactions among different types of biomedical entities (proteins, genes, diseases, drugs, etc.). Several large resources of curated relations between biomedical entities are currently available, such as the Pharmacogenomics Knowledge Base (PharmGKB) or the Comparative Toxicogenomics Database (CTD).Biomedical text mining systems, and in particular those which deal with the extraction of relationships among entities, could make better use of the wealth of already curated material. |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 5% |
| Unknown | 20 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 33% |
| Researcher | 6 | 29% |
| Student > Postgraduate | 2 | 10% |
| Student > Master | 2 | 10% |
| Lecturer | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 1 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 24% |
| Agricultural and Biological Sciences | 3 | 14% |
| Biochemistry, Genetics and Molecular Biology | 2 | 10% |
| Linguistics | 2 | 10% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 10% |
| Other | 3 | 14% |
| Unknown | 4 | 19% |
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 08 August 2023.
All research outputs
#8,534,976
of 25,374,647 outputs
Outputs from Journal of Biomedical Semantics
#155
of 368 outputs
Outputs of similar age
#65,386
of 191,706 outputs
Outputs of similar age from Journal of Biomedical Semantics
#2
of 13 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 368 research outputs from this source. They receive a mean Attention Score of 4.6. This one has gotten more attention than average, scoring higher than 52% 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 191,706 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.