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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Gene set enrichment analysis for multiple continuous phenotypes
|
|---|---|
| Published in |
BMC Bioinformatics, August 2014
|
| DOI | 10.1186/1471-2105-15-260 |
| Pubmed ID | |
| Authors |
Xiaoming Wang, Saumyadipta Pyne, Irina Dinu |
| Abstract |
Gene set analysis (GSA) methods test the association of sets of genes with phenotypes in gene expression microarray studies. While GSA methods on a single binary or categorical phenotype abounds, little attention has been paid to the case of a continuous phenotype, and there is no method to accommodate correlated multiple continuous phenotypes. |
X Demographics
The data shown below were collected from the profiles of 8 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 Kingdom | 1 | 13% |
| Norway | 1 | 13% |
| Unknown | 6 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 50% |
| Members of the public | 3 | 38% |
| Science communicators (journalists, bloggers, editors) | 1 | 13% |
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 Kingdom | 2 | 7% |
| Germany | 1 | 3% |
| Norway | 1 | 3% |
| Netherlands | 1 | 3% |
| Denmark | 1 | 3% |
| Russia | 1 | 3% |
| Unknown | 23 | 77% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 12 | 40% |
| Student > Ph. D. Student | 9 | 30% |
| Student > Master | 2 | 7% |
| Student > Bachelor | 1 | 3% |
| Professor | 1 | 3% |
| Other | 4 | 13% |
| Unknown | 1 | 3% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 30% |
| Biochemistry, Genetics and Molecular Biology | 4 | 13% |
| Chemistry | 4 | 13% |
| Medicine and Dentistry | 4 | 13% |
| Computer Science | 4 | 13% |
| Other | 3 | 10% |
| Unknown | 2 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 04 August 2014.
All research outputs
#12,707,910
of 22,759,618 outputs
Outputs from BMC Bioinformatics
#3,621
of 7,273 outputs
Outputs of similar age
#101,644
of 229,815 outputs
Outputs of similar age from BMC Bioinformatics
#61
of 125 outputs
Altmetric has tracked 22,759,618 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,273 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 48th percentile – i.e., 48% 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 229,815 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 55% of its contemporaries.
We're also able to compare this research output to 125 others from the same source and published within six weeks on either side of this one. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.