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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data
|
|---|---|
| Published in |
BMC Medical Genomics, January 2013
|
| DOI | 10.1186/1755-8794-6-2 |
| Pubmed ID | |
| Authors |
Kristina M Hettne, André Boorsma, Dorien A M van Dartel, Jelle J Goeman, Esther de Jong, Aldert H Piersma, Rob H Stierum, Jos C Kleinjans, Jan A Kors |
| Abstract |
Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with gene set analysis (GSA) methods for chemical treatment identification, for pharmacological mechanism elucidation, and for comparing compound toxicity profiles. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 2 | 3% |
| Spain | 2 | 3% |
| United Kingdom | 1 | 2% |
| United States | 1 | 2% |
| Croatia | 1 | 2% |
| Unknown | 53 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 23 | 38% |
| Student > Ph. D. Student | 10 | 17% |
| Professor | 3 | 5% |
| Student > Master | 3 | 5% |
| Student > Doctoral Student | 2 | 3% |
| Other | 9 | 15% |
| Unknown | 10 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 21 | 35% |
| Computer Science | 7 | 12% |
| Biochemistry, Genetics and Molecular Biology | 5 | 8% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 7% |
| Medicine and Dentistry | 4 | 7% |
| Other | 6 | 10% |
| Unknown | 13 | 22% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 31 January 2020.
All research outputs
#15,557,505
of 23,881,329 outputs
Outputs from BMC Medical Genomics
#629
of 1,268 outputs
Outputs of similar age
#182,332
of 288,412 outputs
Outputs of similar age from BMC Medical Genomics
#10
of 13 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,268 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 45th percentile – i.e., 45% 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 288,412 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 34th percentile – i.e., 34% 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 is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.