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X Demographics
Mendeley readers
Attention Score in Context
| Title |
CodingMotif: exact determination of overrepresented nucleotide motifs in coding sequences
|
|---|---|
| Published in |
BMC Bioinformatics, February 2012
|
| DOI | 10.1186/1471-2105-13-32 |
| Pubmed ID | |
| Authors |
Yang Ding, William A Lorenz, Jeffrey H Chuang |
| Abstract |
It has been increasingly appreciated that coding sequences harbor regulatory sequence motifs in addition to encoding for protein. These sequence motifs are expected to be overrepresented in nucleotide sequences bound by a common protein or small RNA. However, detecting overrepresented motifs has been difficult because of interference by constraints at the protein level. Sampling-based approaches to solve this problem based on codon-shuffling have been limited to exploring only an infinitesimal fraction of the sequence space and by their use of parametric approximations. |
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 Kingdom | 1 | 50% |
| Brazil | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 6% |
| Colombia | 1 | 2% |
| Italy | 1 | 2% |
| France | 1 | 2% |
| Unknown | 47 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 30% |
| Student > Ph. D. Student | 12 | 23% |
| Professor | 4 | 8% |
| Professor > Associate Professor | 4 | 8% |
| Student > Master | 4 | 8% |
| Other | 8 | 15% |
| Unknown | 5 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 22 | 42% |
| Biochemistry, Genetics and Molecular Biology | 15 | 28% |
| Computer Science | 8 | 15% |
| Sports and Recreations | 1 | 2% |
| Engineering | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 6 | 11% |
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 12 March 2012.
All research outputs
#15,242,272
of 22,663,150 outputs
Outputs from BMC Bioinformatics
#5,357
of 7,242 outputs
Outputs of similar age
#165,703
of 250,850 outputs
Outputs of similar age from BMC Bioinformatics
#54
of 67 outputs
Altmetric has tracked 22,663,150 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,242 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 18th percentile – i.e., 18% 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 250,850 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 67 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.