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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Bacterial phylogenetic tree construction based on genomic translation stop signals
|
|---|---|
| Published in |
Microbial Informatics and Experimentation, May 2012
|
| DOI | 10.1186/2042-5783-2-6 |
| Pubmed ID | |
| Authors |
Lijing Xu, Jimmy Kuo, Jong-Kang Liu, Tit-Yee Wong |
| Abstract |
The efficiencies of the stop codons TAA, TAG, and TGA in protein synthesis termination are not the same. These variations could allow many genes to be regulated. There are many similar nucleotide trimers found on the second and third reading-frames of a gene. They are called premature stop codons (PSC). Like stop codons, the PSC in bacterial genomes are also highly bias in terms of their quantities and qualities on the genes. Phylogenetically related species often share a similar PSC profile. We want to know whether the selective forces that influence the stop codons and the PSC usage biases in a genome are related. We also wish to know how strong these trimers in a genome are related to the natural history of the bacterium. Knowing these relations may provide better knowledge in the phylogeny of bacteria |
X Demographics
The data shown below were collected from the profiles of 2 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 States | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| South Africa | 1 | 4% |
| Unknown | 27 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 25% |
| Student > Master | 5 | 18% |
| Researcher | 5 | 18% |
| Student > Bachelor | 4 | 14% |
| Professor | 1 | 4% |
| Other | 2 | 7% |
| Unknown | 4 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 18 | 64% |
| Biochemistry, Genetics and Molecular Biology | 3 | 11% |
| Veterinary Science and Veterinary Medicine | 1 | 4% |
| Medicine and Dentistry | 1 | 4% |
| Design | 1 | 4% |
| Other | 0 | 0% |
| Unknown | 4 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 October 2012.
All research outputs
#17,659,617
of 22,668,244 outputs
Outputs from Microbial Informatics and Experimentation
#14
of 15 outputs
Outputs of similar age
#122,387
of 165,196 outputs
Outputs of similar age from Microbial Informatics and Experimentation
#2
of 2 outputs
Altmetric has tracked 22,668,244 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 15 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.0. This one scored the same or higher as 1 of them.
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 165,196 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.