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 |
GeneFriends: An online co-expression analysis tool to identify novel gene targets for aging and complex diseases
|
|---|---|
| Published in |
BMC Genomics, October 2012
|
| DOI | 10.1186/1471-2164-13-535 |
| Pubmed ID | |
| Authors |
Sipko van Dam, Rui Cordeiro, Thomas Craig, Jesse van Dam, Shona H Wood, João Pedro de Magalhães |
| Abstract |
Although many diseases have been well characterized at the molecular level, the underlying mechanisms are often unknown. Nearly half of all human genes remain poorly studied, yet these genes may contribute to a number of disease processes. Genes involved in common biological processes and diseases are often co-expressed. Using known disease-associated genes in a co-expression analysis may help identify and prioritize novel candidate genes for further study. |
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 % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 101 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 4% |
| Netherlands | 2 | 2% |
| Portugal | 2 | 2% |
| Chile | 1 | <1% |
| Brazil | 1 | <1% |
| China | 1 | <1% |
| Japan | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 88 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 28 | 28% |
| Researcher | 20 | 20% |
| Student > Master | 18 | 18% |
| Student > Bachelor | 7 | 7% |
| Professor > Associate Professor | 5 | 5% |
| Other | 10 | 10% |
| Unknown | 13 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 48 | 48% |
| Biochemistry, Genetics and Molecular Biology | 17 | 17% |
| Computer Science | 6 | 6% |
| Medicine and Dentistry | 4 | 4% |
| Neuroscience | 2 | 2% |
| Other | 5 | 5% |
| Unknown | 19 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 25 February 2019.
All research outputs
#2,381,353
of 22,687,320 outputs
Outputs from BMC Genomics
#758
of 10,616 outputs
Outputs of similar age
#17,131
of 172,657 outputs
Outputs of similar age from BMC Genomics
#12
of 131 outputs
Altmetric has tracked 22,687,320 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,616 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 92% 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 172,657 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 131 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 90% of its contemporaries.