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Twitter Demographics
Mendeley readers
Attention Score in Context
| Title |
Composite effects of gene determinants on the translation speed and density of ribosomes
|
|---|---|
| Published in |
Genome Biology, January 2011
|
| DOI | 10.1186/gb-2011-12-11-r110 |
| Pubmed ID | |
| Authors |
Tamir Tuller, Isana Veksler-Lublinsky, Nir Gazit, Martin Kupiec, Eytan Ruppin, Michal Ziv-Ukelson |
| Abstract |
Translation is a central process of life, and its regulation is crucial for cell growth. In this article, focusing on two model organisms, Escherichia coli and Saccharomyces cerevisiae, we study how three major local features of a gene's coding sequence (its adaptation to the tRNA pool, its amino acid charge, and its mRNA folding energy) affect its translation elongation. |
Twitter Demographics
The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 163 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 4% |
| United Kingdom | 3 | 2% |
| Spain | 2 | 1% |
| Sweden | 1 | <1% |
| France | 1 | <1% |
| Russia | 1 | <1% |
| Netherlands | 1 | <1% |
| Japan | 1 | <1% |
| China | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 146 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 48 | 29% |
| Researcher | 44 | 27% |
| Student > Master | 17 | 10% |
| Professor > Associate Professor | 6 | 4% |
| Student > Bachelor | 6 | 4% |
| Other | 18 | 11% |
| Unknown | 24 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 72 | 44% |
| Biochemistry, Genetics and Molecular Biology | 38 | 23% |
| Engineering | 7 | 4% |
| Computer Science | 4 | 2% |
| Physics and Astronomy | 3 | 2% |
| Other | 11 | 7% |
| Unknown | 28 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 01 February 2022.
All research outputs
#7,438,907
of 24,003,070 outputs
Outputs from Genome Biology
#3,218
of 4,279 outputs
Outputs of similar age
#52,942
of 186,794 outputs
Outputs of similar age from Genome Biology
#89
of 140 outputs
Altmetric has tracked 24,003,070 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 4,279 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.9. This one is in the 23rd percentile – i.e., 23% 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 186,794 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 70% of its contemporaries.
We're also able to compare this research output to 140 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.