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X Demographics
Mendeley readers
Attention Score in Context
| Title |
TurboFold: Iterative probabilistic estimation of secondary structures for multiple RNA sequences
|
|---|---|
| Published in |
BMC Bioinformatics, April 2011
|
| DOI | 10.1186/1471-2105-12-108 |
| Pubmed ID | |
| Authors |
Arif O Harmanci, Gaurav Sharma, David H Mathews |
| Abstract |
The prediction of secondary structure, i.e. the set of canonical base pairs between nucleotides, is a first step in developing an understanding of the function of an RNA sequence. The most accurate computational methods predict conserved structures for a set of homologous RNA sequences. These methods usually suffer from high computational complexity. In this paper, TurboFold, a novel and efficient method for secondary structure prediction for multiple RNA sequences, is presented. |
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 % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 4% |
| France | 2 | 2% |
| Brazil | 2 | 2% |
| Germany | 1 | 1% |
| Australia | 1 | 1% |
| Unknown | 75 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 22 | 26% |
| Student > Ph. D. Student | 20 | 24% |
| Student > Master | 12 | 14% |
| Professor > Associate Professor | 8 | 10% |
| Student > Bachelor | 7 | 8% |
| Other | 12 | 14% |
| Unknown | 3 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 38 | 45% |
| Biochemistry, Genetics and Molecular Biology | 14 | 17% |
| Computer Science | 11 | 13% |
| Immunology and Microbiology | 5 | 6% |
| Engineering | 5 | 6% |
| Other | 7 | 8% |
| Unknown | 4 | 5% |
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 22 July 2015.
All research outputs
#6,414,147
of 22,789,076 outputs
Outputs from BMC Bioinformatics
#2,472
of 7,279 outputs
Outputs of similar age
#34,622
of 109,241 outputs
Outputs of similar age from BMC Bioinformatics
#23
of 64 outputs
Altmetric has tracked 22,789,076 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 7,279 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 65% 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 109,241 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 66% of its contemporaries.
We're also able to compare this research output to 64 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 60% of its contemporaries.