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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Down-weighting overlapping genes improves gene set analysis
|
|---|---|
| Published in |
BMC Bioinformatics, June 2012
|
| DOI | 10.1186/1471-2105-13-136 |
| Pubmed ID | |
| Authors |
Adi Laurentiu Tarca, Sorin Draghici, Gaurav Bhatti, Roberto Romero |
| Abstract |
The identification of gene sets that are significantly impacted in a given condition based on microarray data is a crucial step in current life science research. Most gene set analysis methods treat genes equally, regardless how specific they are to a given gene set. |
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 % |
|---|---|---|
| Spain | 1 | 50% |
| United States | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 138 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 2% |
| Germany | 1 | <1% |
| Australia | 1 | <1% |
| Netherlands | 1 | <1% |
| Brazil | 1 | <1% |
| Luxembourg | 1 | <1% |
| Unknown | 130 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 44 | 32% |
| Student > Ph. D. Student | 37 | 27% |
| Student > Master | 14 | 10% |
| Student > Bachelor | 8 | 6% |
| Professor > Associate Professor | 5 | 4% |
| Other | 16 | 12% |
| Unknown | 14 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 49 | 36% |
| Biochemistry, Genetics and Molecular Biology | 30 | 22% |
| Computer Science | 19 | 14% |
| Medicine and Dentistry | 4 | 3% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 2% |
| Other | 14 | 10% |
| Unknown | 19 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 24 June 2020.
All research outputs
#6,109,554
of 22,668,244 outputs
Outputs from BMC Bioinformatics
#2,323
of 7,247 outputs
Outputs of similar age
#42,642
of 164,469 outputs
Outputs of similar age from BMC Bioinformatics
#35
of 105 outputs
Altmetric has tracked 22,668,244 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 7,247 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 67% 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 164,469 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 105 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.