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X Demographics
Mendeley readers
Attention Score in Context
| Title |
LeARN: a platform for detecting, clustering and annotating non-coding RNAs
|
|---|---|
| Published in |
BMC Bioinformatics, January 2008
|
| DOI | 10.1186/1471-2105-9-21 |
| Pubmed ID | |
| Authors |
Céline Noirot, Christine Gaspin, Thomas Schiex, Jérôme Gouzy |
| Abstract |
In the last decade, sequencing projects have led to the development of a number of annotation systems dedicated to the structural and functional annotation of protein-coding genes. These annotation systems manage the annotation of the non-protein coding genes (ncRNAs) in a very crude way, allowing neither the edition of the secondary structures nor the clustering of ncRNA genes into families which are crucial for appropriate annotation of these molecules. |
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 % |
|---|---|---|
| India | 1 | 33% |
| France | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 2 | 3% |
| Canada | 2 | 3% |
| United States | 2 | 3% |
| United Kingdom | 1 | 2% |
| Norway | 1 | 2% |
| Sweden | 1 | 2% |
| Poland | 1 | 2% |
| Unknown | 50 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 22 | 37% |
| Student > Ph. D. Student | 15 | 25% |
| Student > Postgraduate | 4 | 7% |
| Professor | 3 | 5% |
| Student > Master | 3 | 5% |
| Other | 7 | 12% |
| Unknown | 6 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 40 | 67% |
| Computer Science | 8 | 13% |
| Biochemistry, Genetics and Molecular Biology | 4 | 7% |
| Engineering | 1 | 2% |
| Unknown | 7 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 19 May 2018.
All research outputs
#3,625,012
of 22,671,366 outputs
Outputs from BMC Bioinformatics
#1,346
of 7,247 outputs
Outputs of similar age
#17,302
of 156,461 outputs
Outputs of similar age from BMC Bioinformatics
#9
of 38 outputs
Altmetric has tracked 22,671,366 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
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 done well, scoring higher than 81% 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 156,461 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 88% of its contemporaries.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.