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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Modelling mutational and selection pressures on dinucleotides in eukaryotic phyla –selection against CpG and UpA in cytoplasmically expressed RNA and in RNA viruses
|
|---|---|
| Published in |
BMC Genomics, September 2013
|
| DOI | 10.1186/1471-2164-14-610 |
| Pubmed ID | |
| Authors |
Peter Simmonds, Wenjun Xia, J Kenneth Baillie, Ken McKinnon |
| Abstract |
Loss of CpG dinucleotides in genomic DNA through methylation-induced mutation is characteristic of vertebrates and plants. However, these and other eukaryotic phyla show a range of other dinucleotide frequency biases with currently uncharacterized underlying mutational or selection mechanisms. We developed a parameterized Markov process to identify what neighbour context-dependent mutations best accounted for patterns of dinucleotide frequency biases in genomic and cytoplasmically expressed mRNA sequences of different vertebrates, other eukaryotic groups and RNA viruses that infect them. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 2% |
| United States | 2 | 2% |
| Unknown | 84 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 19% |
| Student > Master | 17 | 19% |
| Researcher | 15 | 17% |
| Student > Bachelor | 13 | 15% |
| Student > Doctoral Student | 5 | 6% |
| Other | 12 | 14% |
| Unknown | 9 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 27 | 31% |
| Biochemistry, Genetics and Molecular Biology | 21 | 24% |
| Immunology and Microbiology | 10 | 11% |
| Computer Science | 4 | 5% |
| Chemical Engineering | 3 | 3% |
| Other | 9 | 10% |
| Unknown | 14 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 27 December 2022.
All research outputs
#5,240,151
of 25,373,627 outputs
Outputs from BMC Genomics
#2,029
of 11,244 outputs
Outputs of similar age
#43,234
of 210,783 outputs
Outputs of similar age from BMC Genomics
#34
of 207 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 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 81% 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 210,783 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 79% of its contemporaries.
We're also able to compare this research output to 207 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.