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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Global mRNA selection mechanisms for translation initiation
|
|---|---|
| Published in |
Genome Biology, January 2015
|
| DOI | 10.1186/s13059-014-0559-z |
| Pubmed ID | |
| Authors |
Joseph Costello, Lydia M Castelli, William Rowe, Christopher J Kershaw, David Talavera, Sarah S Mohammad-Qureshi, Paul F G Sims, Christopher M Grant, Graham D Pavitt, Simon J Hubbard, Mark P Ashe |
| Abstract |
The selection and regulation of individual mRNAs for translation initiation from a competing pool of mRNA are poorly understood processes. The closed loop complex, comprising eIF4E, eIF4G and PABP, and its regulation by 4E-BPs are perceived to be key players. Using RIP-seq, we aimed to evaluate the role in gene regulation of the closed loop complex and 4E-BP regulation across the entire yeast transcriptome. |
X Demographics
The data shown below were collected from the profiles of 10 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 | 2 | 20% |
| Japan | 1 | 10% |
| United States | 1 | 10% |
| United Kingdom | 1 | 10% |
| Unknown | 5 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 70% |
| Scientists | 2 | 20% |
| Science communicators (journalists, bloggers, editors) | 1 | 10% |
Mendeley readers
The data shown below were compiled from readership statistics for 158 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 | 155 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 37 | 23% |
| Researcher | 30 | 19% |
| Student > Master | 19 | 12% |
| Student > Bachelor | 16 | 10% |
| Professor | 13 | 8% |
| Other | 29 | 18% |
| Unknown | 14 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 72 | 46% |
| Agricultural and Biological Sciences | 53 | 34% |
| Computer Science | 4 | 3% |
| Physics and Astronomy | 3 | 2% |
| Neuroscience | 2 | 1% |
| Other | 7 | 4% |
| Unknown | 17 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 11 November 2020.
All research outputs
#4,788,678
of 25,374,647 outputs
Outputs from Genome Biology
#2,781
of 4,467 outputs
Outputs of similar age
#61,617
of 358,856 outputs
Outputs of similar age from Genome Biology
#70
of 91 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
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 37th percentile – i.e., 37% 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 358,856 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 82% of its contemporaries.
We're also able to compare this research output to 91 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.