Title |
CBESW: Sequence Alignment on the Playstation 3
|
---|---|
Published in |
BMC Bioinformatics, September 2008
|
DOI | 10.1186/1471-2105-9-377 |
Pubmed ID | |
Authors |
Adrianto Wirawan, Chee Keong Kwoh, Nim Tri Hieu, Bertil Schmidt |
Abstract |
The exponential growth of available biological data has caused bioinformatics to be rapidly moving towards a data-intensive, computational science. As a result, the computational power needed by bioinformatics applications is growing exponentially as well. The recent emergence of accelerator technologies has made it possible to achieve an excellent improvement in execution time for many bioinformatics applications, compared to current general-purpose platforms. In this paper, we demonstrate how the PlayStation 3, powered by the Cell Broadband Engine, can be used as a computational platform to accelerate the Smith-Waterman algorithm. |
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 % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Japan | 2 | 5% |
Germany | 1 | 3% |
Netherlands | 1 | 3% |
France | 1 | 3% |
Italy | 1 | 3% |
Malaysia | 1 | 3% |
United Kingdom | 1 | 3% |
Brazil | 1 | 3% |
United States | 1 | 3% |
Other | 1 | 3% |
Unknown | 29 | 73% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 11 | 28% |
Student > Master | 10 | 25% |
Student > Ph. D. Student | 8 | 20% |
Professor | 3 | 8% |
Student > Bachelor | 2 | 5% |
Other | 4 | 10% |
Unknown | 2 | 5% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 17 | 43% |
Computer Science | 14 | 35% |
Medicine and Dentistry | 3 | 8% |
Engineering | 2 | 5% |
Arts and Humanities | 1 | 3% |
Other | 1 | 3% |
Unknown | 2 | 5% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 08 November 2016.
All research outputs
#4,099,821
of 24,666,614 outputs
Outputs from BMC Bioinformatics
#1,456
of 7,565 outputs
Outputs of similar age
#14,925
of 94,220 outputs
Outputs of similar age from BMC Bioinformatics
#9
of 39 outputs
Altmetric has tracked 24,666,614 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,565 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 80% 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 94,220 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 84% of its contemporaries.
We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.