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Mendeley readers
Attention Score in Context
| Title |
Anatomy of Escherichia coli ribosome binding sites11Edited by D. Draper
|
|---|---|
| Published in |
Journal of Molecular Biology, October 2001
|
| DOI | 10.1006/jmbi.2001.5040 |
| Pubmed ID | |
| Authors |
Ryan K Shultzaberger, R.Elaine Bucheimer, Kenneth E Rudd, Thomas D Schneider |
| Abstract |
During translational initiation in prokaryotes, the 3' end of the 16S rRNA binds to a region just upstream of the initiation codon. The relationship between this Shine-Dalgarno (SD) region and the binding of ribosomes to translation start-points has been well studied, but a unified mathematical connection between the SD, the initiation codon and the spacing between them has been lacking. Using information theory, we constructed a model that treats these three components uniformly by assigning to the SD and the initiation region (IR) conservations in bits of information, and by assigning to the spacing an uncertainty, also in bits. To build the model, we first aligned the SD region by maximizing the information content there. The ease of this process confirmed the existence of the SD pattern within a set of 4122 reviewed and revised Escherichia coli gene starts. This large data set allowed us to show graphically, by sequence logos, that the spacing between the SD and the initiation region affects both the SD site conservation and its pattern. We used the aligned SD, the spacing, and the initiation region to model ribosome binding and to identify gene starts that do not conform to the ribosome binding site model. A total of 569 experimentally proven starts are more conserved (have higher information content) than the full set of revised starts, which probably reflects an experimental bias against the detection of gene products that have inefficient ribosome binding sites. Models were refined cyclically by removing non-conforming weak sites. After this procedure, models derived from either the original or the revised gene start annotation were similar. Therefore, this information theory-based technique provides a method for easily constructing biologically sensible ribosome binding site models. Such models should be useful for refining gene-start predictions of any sequenced bacterial genome. |
Mendeley readers
The data shown below were compiled from readership statistics for 200 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 4% |
| Spain | 3 | 2% |
| Germany | 2 | 1% |
| Australia | 1 | <1% |
| Israel | 1 | <1% |
| United Kingdom | 1 | <1% |
| Iran, Islamic Republic of | 1 | <1% |
| Mexico | 1 | <1% |
| Malaysia | 1 | <1% |
| Other | 4 | 2% |
| Unknown | 177 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 50 | 25% |
| Researcher | 50 | 25% |
| Student > Master | 26 | 13% |
| Student > Bachelor | 20 | 10% |
| Student > Doctoral Student | 13 | 7% |
| Other | 28 | 14% |
| Unknown | 13 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 103 | 52% |
| Biochemistry, Genetics and Molecular Biology | 50 | 25% |
| Engineering | 7 | 4% |
| Computer Science | 7 | 4% |
| Chemistry | 6 | 3% |
| Other | 12 | 6% |
| Unknown | 15 | 8% |
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 26 January 2016.
All research outputs
#3,798,611
of 25,373,627 outputs
Outputs from Journal of Molecular Biology
#1,119
of 11,922 outputs
Outputs of similar age
#4,224
of 44,625 outputs
Outputs of similar age from Journal of Molecular Biology
#7
of 113 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,922 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done well, scoring higher than 84% 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 44,625 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 86% of its contemporaries.
We're also able to compare this research output to 113 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.