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X Demographics
Mendeley readers
Attention Score in Context
| Title |
GOToolBox: functional analysis of gene datasets based on Gene Ontology
|
|---|---|
| Published in |
Genome Biology, November 2004
|
| DOI | 10.1186/gb-2004-5-12-r101 |
| Pubmed ID | |
| Authors |
David Martin, Christine Brun, Elisabeth Remy, Pierre Mouren, Denis Thieffry, Bernard Jacq |
| Abstract |
We have developed methods and tools based on the Gene Ontology (GO) resource allowing the identification of statistically over- or under-represented terms in a gene dataset; the clustering of functionally related genes within a set; and the retrieval of genes sharing annotations with a query gene. GO annotations can also be constrained to a slim hierarchy or a given level of the ontology. The source codes are available upon request, and distributed under the GPL license. |
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 % |
|---|---|---|
| India | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 274 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 3% |
| Germany | 3 | 1% |
| Portugal | 2 | <1% |
| United Kingdom | 2 | <1% |
| France | 2 | <1% |
| Italy | 2 | <1% |
| Norway | 1 | <1% |
| Switzerland | 1 | <1% |
| Hong Kong | 1 | <1% |
| Other | 10 | 4% |
| Unknown | 242 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 71 | 26% |
| Student > Ph. D. Student | 61 | 22% |
| Student > Master | 30 | 11% |
| Student > Bachelor | 25 | 9% |
| Professor > Associate Professor | 19 | 7% |
| Other | 45 | 16% |
| Unknown | 23 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 134 | 49% |
| Biochemistry, Genetics and Molecular Biology | 40 | 15% |
| Computer Science | 35 | 13% |
| Medicine and Dentistry | 10 | 4% |
| Engineering | 8 | 3% |
| Other | 20 | 7% |
| Unknown | 27 | 10% |
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 28 July 2022.
All research outputs
#7,047,742
of 25,374,647 outputs
Outputs from Genome Biology
#3,232
of 4,467 outputs
Outputs of similar age
#31,272
of 152,893 outputs
Outputs of similar age from Genome Biology
#12
of 27 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 27th percentile – i.e., 27% 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 152,893 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 79% of its contemporaries.
We're also able to compare this research output to 27 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 55% of its contemporaries.