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X Demographics
Mendeley readers
Attention Score in Context
Title |
High-throughput sequence alignment using Graphics Processing Units
|
---|---|
Published in |
BMC Bioinformatics, December 2007
|
DOI | 10.1186/1471-2105-8-474 |
Pubmed ID | |
Authors |
Michael C Schatz, Cole Trapnell, Arthur L Delcher, Amitabh Varshney |
Abstract |
The recent availability of new, less expensive high-throughput DNA sequencing technologies has yielded a dramatic increase in the volume of sequence data that must be analyzed. These data are being generated for several purposes, including genotyping, genome resequencing, metagenomics, and de novo genome assembly projects. Sequence alignment programs such as MUMmer have proven essential for analysis of these data, but researchers will need ever faster, high-throughput alignment tools running on inexpensive hardware to keep up with new sequence technologies. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 67% |
Spain | 1 | 17% |
Unknown | 1 | 17% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 4 | 67% |
Members of the public | 2 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 371 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 28 | 8% |
Brazil | 8 | 2% |
France | 5 | 1% |
Canada | 5 | 1% |
United Kingdom | 5 | 1% |
Germany | 4 | 1% |
Italy | 3 | <1% |
Hong Kong | 2 | <1% |
Sweden | 2 | <1% |
Other | 18 | 5% |
Unknown | 291 | 78% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 105 | 28% |
Student > Ph. D. Student | 79 | 21% |
Student > Master | 50 | 13% |
Professor > Associate Professor | 27 | 7% |
Professor | 23 | 6% |
Other | 62 | 17% |
Unknown | 25 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 157 | 42% |
Computer Science | 106 | 29% |
Biochemistry, Genetics and Molecular Biology | 26 | 7% |
Engineering | 17 | 5% |
Medicine and Dentistry | 11 | 3% |
Other | 24 | 6% |
Unknown | 30 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 12 December 2023.
All research outputs
#3,639,021
of 25,463,724 outputs
Outputs from BMC Bioinformatics
#1,214
of 7,704 outputs
Outputs of similar age
#14,203
of 167,175 outputs
Outputs of similar age from BMC Bioinformatics
#9
of 46 outputs
Altmetric has tracked 25,463,724 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,704 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 84% 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 167,175 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.