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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Protein-specific prediction of mRNA binding using RNA sequences, binding motifs and predicted secondary structures
|
|---|---|
| Published in |
BMC Bioinformatics, April 2014
|
| DOI | 10.1186/1471-2105-15-123 |
| Pubmed ID | |
| Authors |
Carmen M Livi, Enrico Blanzieri |
| Abstract |
RNA-binding proteins interact with specific RNA molecules to regulate important cellular processes. It is therefore necessary to identify the RNA interaction partners in order to understand the precise functions of such proteins. Protein-RNA interactions are typically characterized using in vivo and in vitro experiments but these may not detect all binding partners. Therefore, computational methods that capture the protein-dependent nature of such binding interactions could help to predict potential binding partners in silico. |
X Demographics
The data shown below were collected from the profiles of 5 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 | 2 | 40% |
| United States | 1 | 20% |
| Norway | 1 | 20% |
| France | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| Spain | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 71 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 22 | 30% |
| Researcher | 14 | 19% |
| Student > Master | 8 | 11% |
| Student > Bachelor | 5 | 7% |
| Professor > Associate Professor | 5 | 7% |
| Other | 11 | 15% |
| Unknown | 9 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 27 | 36% |
| Biochemistry, Genetics and Molecular Biology | 14 | 19% |
| Computer Science | 12 | 16% |
| Neuroscience | 2 | 3% |
| Engineering | 2 | 3% |
| Other | 6 | 8% |
| Unknown | 11 | 15% |
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 09 May 2014.
All research outputs
#13,408,116
of 22,754,104 outputs
Outputs from BMC Bioinformatics
#4,189
of 7,269 outputs
Outputs of similar age
#112,198
of 227,503 outputs
Outputs of similar age from BMC Bioinformatics
#68
of 136 outputs
Altmetric has tracked 22,754,104 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,269 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 38th percentile – i.e., 38% 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 227,503 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 136 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.