You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
A gene signature for post-infectious chronic fatigue syndrome
|
|---|---|
| Published in |
BMC Medical Genomics, June 2009
|
| DOI | 10.1186/1755-8794-2-38 |
| Pubmed ID | |
| Authors |
John W Gow, Suzanne Hagan, Pawel Herzyk, Celia Cannon, Peter O Behan, Abhijit Chaudhuri |
| Abstract |
At present, there are no clinically reliable disease markers for chronic fatigue syndrome. DNA chip microarray technology provides a method for examining the differential expression of mRNA from a large number of genes. Our hypothesis was that a gene expression signature, generated by microarray assays, could help identify genes which are dysregulated in patients with post-infectious CFS and so help identify biomarkers for the condition. |
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 % |
|---|---|---|
| United States | 2 | 33% |
| United Kingdom | 2 | 33% |
| Unknown | 2 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Practitioners (doctors, other healthcare professionals) | 2 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 3% |
| United Kingdom | 1 | 1% |
| Unknown | 66 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 22% |
| Student > Ph. D. Student | 10 | 14% |
| Student > Master | 7 | 10% |
| Student > Doctoral Student | 6 | 9% |
| Student > Bachelor | 4 | 6% |
| Other | 17 | 25% |
| Unknown | 10 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 15 | 22% |
| Agricultural and Biological Sciences | 13 | 19% |
| Psychology | 7 | 10% |
| Biochemistry, Genetics and Molecular Biology | 5 | 7% |
| Immunology and Microbiology | 4 | 6% |
| Other | 12 | 17% |
| Unknown | 13 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 18 September 2019.
All research outputs
#2,897,673
of 22,649,029 outputs
Outputs from BMC Medical Genomics
#123
of 1,211 outputs
Outputs of similar age
#11,147
of 111,103 outputs
Outputs of similar age from BMC Medical Genomics
#1
of 12 outputs
Altmetric has tracked 22,649,029 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,211 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 89% 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 111,103 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 89% of its contemporaries.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.