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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Disk-based k-mer counting on a PC
|
|---|---|
| Published in |
BMC Bioinformatics, May 2013
|
| DOI | 10.1186/1471-2105-14-160 |
| Pubmed ID | |
| Authors |
Sebastian Deorowicz, Agnieszka Debudaj-Grabysz, Szymon Grabowski |
| Abstract |
The k-mer counting problem, which is to build the histogram of occurrences of every k-symbol long substring in a given text, is important for many bioinformatics applications. They include developing de Bruijn graph genome assemblers, fast multiple sequence alignment and repeat detection. |
X Demographics
The data shown below were collected from the profiles of 9 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 | 3 | 33% |
| Germany | 2 | 22% |
| Norway | 1 | 11% |
| United Kingdom | 1 | 11% |
| Unknown | 2 | 22% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 5 | 56% |
| Members of the public | 4 | 44% |
Mendeley readers
The data shown below were compiled from readership statistics for 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 8 | 8% |
| Germany | 1 | 1% |
| Brazil | 1 | 1% |
| France | 1 | 1% |
| Argentina | 1 | 1% |
| India | 1 | 1% |
| Unknown | 86 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 26 | 26% |
| Researcher | 24 | 24% |
| Student > Master | 14 | 14% |
| Student > Bachelor | 9 | 9% |
| Professor > Associate Professor | 6 | 6% |
| Other | 12 | 12% |
| Unknown | 8 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 32 | 32% |
| Computer Science | 28 | 28% |
| Biochemistry, Genetics and Molecular Biology | 14 | 14% |
| Medicine and Dentistry | 5 | 5% |
| Engineering | 3 | 3% |
| Other | 6 | 6% |
| Unknown | 11 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 17. 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 11 September 2013.
All research outputs
#2,026,311
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#499
of 7,400 outputs
Outputs of similar age
#17,455
of 196,435 outputs
Outputs of similar age from BMC Bioinformatics
#14
of 127 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,400 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 particularly well, scoring higher than 93% 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 196,435 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 127 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.