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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Faster algorithms for RNA-folding using the Four-Russians method
|
|---|---|
| Published in |
Algorithms for Molecular Biology, March 2014
|
| DOI | 10.1186/1748-7188-9-5 |
| Pubmed ID | |
| Authors |
Balaji Venkatachalam, Dan Gusfield, Yelena Frid |
| Abstract |
The secondary structure that maximizes the number of non-crossing matchings between complimentary bases of an RNA sequence of length n can be computed in O(n3) time using Nussinov's dynamic programming algorithm. The Four-Russians method is a technique that reduces the running time for certain dynamic programming algorithms by a multiplicative factor after a preprocessing step where solutions to all smaller subproblems of a fixed size are exhaustively enumerated and solved. Frid and Gusfield designed an O(n3logn) algorithm for RNA folding using the Four-Russians technique. In their algorithm the preprocessing is interleaved with the algorithm computation. |
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 % |
|---|---|---|
| France | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 7% |
| Unknown | 13 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 29% |
| Researcher | 2 | 14% |
| Student > Bachelor | 1 | 7% |
| Professor | 1 | 7% |
| Student > Ph. D. Student | 1 | 7% |
| Other | 3 | 21% |
| Unknown | 2 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 6 | 43% |
| Agricultural and Biological Sciences | 2 | 14% |
| Business, Management and Accounting | 1 | 7% |
| Biochemistry, Genetics and Molecular Biology | 1 | 7% |
| Sports and Recreations | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 3 | 21% |
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 19 May 2014.
All research outputs
#17,715,061
of 22,747,498 outputs
Outputs from Algorithms for Molecular Biology
#173
of 264 outputs
Outputs of similar age
#153,795
of 221,372 outputs
Outputs of similar age from Algorithms for Molecular Biology
#9
of 9 outputs
Altmetric has tracked 22,747,498 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 264 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 25th percentile – i.e., 25% 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 221,372 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one.