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X Demographics
Mendeley readers
Attention Score in Context
| Title |
CUDASW++ 3.0: accelerating Smith-Waterman protein database search by coupling CPU and GPU SIMD instructions
|
|---|---|
| Published in |
BMC Bioinformatics, April 2013
|
| DOI | 10.1186/1471-2105-14-117 |
| Pubmed ID | |
| Authors |
Yongchao Liu, Adrianto Wirawan, Bertil Schmidt |
| Abstract |
The maximal sensitivity for local alignments makes the Smith-Waterman algorithm a popular choice for protein sequence database search based on pairwise alignment. However, the algorithm is compute-intensive due to a quadratic time complexity. Corresponding runtimes are further compounded by the rapid growth of sequence databases. |
X Demographics
The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 3 | 30% |
| United Kingdom | 2 | 20% |
| Japan | 2 | 20% |
| United States | 2 | 20% |
| Unknown | 1 | 10% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 6 | 60% |
| Members of the public | 4 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Portugal | 1 | 1% |
| Germany | 1 | 1% |
| France | 1 | 1% |
| Norway | 1 | 1% |
| Sweden | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 83 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 23 | 26% |
| Student > Master | 17 | 19% |
| Researcher | 14 | 16% |
| Professor > Associate Professor | 8 | 9% |
| Student > Bachelor | 6 | 7% |
| Other | 17 | 19% |
| Unknown | 4 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 42 | 47% |
| Agricultural and Biological Sciences | 17 | 19% |
| Engineering | 12 | 13% |
| Biochemistry, Genetics and Molecular Biology | 6 | 7% |
| Medicine and Dentistry | 2 | 2% |
| Other | 4 | 4% |
| Unknown | 6 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 10 December 2022.
All research outputs
#4,068,175
of 23,312,088 outputs
Outputs from BMC Bioinformatics
#1,539
of 7,384 outputs
Outputs of similar age
#34,584
of 201,166 outputs
Outputs of similar age from BMC Bioinformatics
#31
of 142 outputs
Altmetric has tracked 23,312,088 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,384 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 done well, scoring higher than 79% 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 201,166 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 142 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.