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X Demographics
Mendeley readers
Attention Score in Context
Title |
A fast structural multiple alignment method for long RNA sequences
|
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Published in |
BMC Bioinformatics, January 2008
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DOI | 10.1186/1471-2105-9-33 |
Pubmed ID | |
Authors |
Yasuo Tabei, Hisanori Kiryu, Taishin Kin, Kiyoshi Asai |
Abstract |
Aligning multiple RNA sequences is essential for analyzing non-coding RNAs. Although many alignment methods for non-coding RNAs, including Sankoff's algorithm for strict structural alignments, have been proposed, they are either inaccurate or computationally too expensive. Faster methods with reasonable accuracies are required for genome-scale analyses. |
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 % |
---|---|---|
Japan | 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 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 2 | 3% |
Brazil | 2 | 3% |
Spain | 2 | 3% |
United States | 2 | 3% |
Denmark | 1 | 1% |
Sweden | 1 | 1% |
Japan | 1 | 1% |
Canada | 1 | 1% |
Unknown | 65 | 84% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 20 | 26% |
Student > Ph. D. Student | 16 | 21% |
Student > Master | 15 | 19% |
Student > Bachelor | 5 | 6% |
Student > Doctoral Student | 5 | 6% |
Other | 9 | 12% |
Unknown | 7 | 9% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 35 | 45% |
Biochemistry, Genetics and Molecular Biology | 13 | 17% |
Computer Science | 13 | 17% |
Environmental Science | 3 | 4% |
Immunology and Microbiology | 1 | 1% |
Other | 3 | 4% |
Unknown | 9 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 17 March 2012.
All research outputs
#6,378,772
of 22,663,969 outputs
Outputs from BMC Bioinformatics
#2,469
of 7,246 outputs
Outputs of similar age
#35,625
of 155,059 outputs
Outputs of similar age from BMC Bioinformatics
#14
of 37 outputs
Altmetric has tracked 22,663,969 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 7,246 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 64% 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 155,059 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.