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X Demographics
Mendeley readers
Attention Score in Context
Title |
Multiple organism algorithm for finding ultraconserved elements
|
---|---|
Published in |
BMC Bioinformatics, January 2008
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DOI | 10.1186/1471-2105-9-15 |
Pubmed ID | |
Authors |
Scott Christley, Neil F Lobo, Greg Madey |
Abstract |
Ultraconserved elements are nucleotide or protein sequences with 100% identity (no mismatches, insertions, or deletions) in the same organism or between two or more organisms. Studies indicate that these conserved regions are associated with micro RNAs, mRNA processing, development and transcription regulation. The identification and characterization of these elements among genomes is necessary for the further understanding of their functionality. |
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 | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 2 | 4% |
Switzerland | 1 | 2% |
Brazil | 1 | 2% |
Italy | 1 | 2% |
Belgium | 1 | 2% |
Poland | 1 | 2% |
Unknown | 40 | 85% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 18 | 38% |
Student > Ph. D. Student | 11 | 23% |
Student > Doctoral Student | 4 | 9% |
Student > Bachelor | 4 | 9% |
Professor > Associate Professor | 4 | 9% |
Other | 7 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 31 | 66% |
Computer Science | 4 | 9% |
Biochemistry, Genetics and Molecular Biology | 3 | 6% |
Environmental Science | 2 | 4% |
Engineering | 2 | 4% |
Other | 6 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 13 May 2013.
All research outputs
#13,361,046
of 22,665,794 outputs
Outputs from BMC Bioinformatics
#4,188
of 7,247 outputs
Outputs of similar age
#127,649
of 155,975 outputs
Outputs of similar age from BMC Bioinformatics
#28
of 38 outputs
Altmetric has tracked 22,665,794 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,247 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 38th percentile – i.e., 38% 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 155,975 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.