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X Demographics
Mendeley readers
Attention Score in Context
| Title |
gsGator: an integrated web platform for cross-species gene set analysis
|
|---|---|
| Published in |
BMC Bioinformatics, January 2014
|
| DOI | 10.1186/1471-2105-15-13 |
| Pubmed ID | |
| Authors |
Hyunjung Kang, Ikjung Choi, Sooyoung Cho, Daeun Ryu, Sanghyuk Lee, Wankyu Kim |
| Abstract |
Gene set analysis (GSA) is useful in deducing biological significance of gene lists using a priori defined gene sets such as gene ontology (GO) or pathways. Phenotypic annotation is sparse for human genes, but is far more abundant for other model organisms such as mouse, fly, and worm. Often, GSA needs to be done highly interactively by combining or modifying gene lists or inspecting gene-gene interactions in a molecular network. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 33% |
| Norway | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 3% |
| Russia | 1 | 3% |
| Unknown | 28 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 37% |
| Student > Ph. D. Student | 7 | 23% |
| Professor > Associate Professor | 3 | 10% |
| Student > Bachelor | 2 | 7% |
| Student > Postgraduate | 2 | 7% |
| Other | 5 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 15 | 50% |
| Biochemistry, Genetics and Molecular Biology | 8 | 27% |
| Computer Science | 3 | 10% |
| Medicine and Dentistry | 1 | 3% |
| Chemistry | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 1 | 3% |
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 20 January 2014.
All research outputs
#14,187,012
of 22,739,983 outputs
Outputs from BMC Bioinformatics
#4,720
of 7,266 outputs
Outputs of similar age
#173,758
of 306,547 outputs
Outputs of similar age from BMC Bioinformatics
#56
of 101 outputs
Altmetric has tracked 22,739,983 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,266 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 30th percentile – i.e., 30% 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 306,547 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 101 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.