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X Demographics
Mendeley readers
Attention Score in Context
| Title |
RAPSearch: a fast protein similarity search tool for short reads
|
|---|---|
| Published in |
BMC Bioinformatics, May 2011
|
| DOI | 10.1186/1471-2105-12-159 |
| Pubmed ID | |
| Authors |
Yuzhen Ye, Jeong-Hyeon Choi, Haixu Tang |
| Abstract |
Next Generation Sequencing (NGS) is producing enormous corpuses of short DNA reads, affecting emerging fields like metagenomics. Protein similarity search--a key step to achieve annotation of protein-coding genes in these short reads, and identification of their biological functions--faces daunting challenges because of the very sizes of the short read datasets. |
X Demographics
The data shown below were collected from the profiles of 3 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 | 1 | 33% |
| United Kingdom | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 67% |
| Members of the public | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 241 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 2% |
| Sweden | 4 | 2% |
| Brazil | 3 | 1% |
| France | 3 | 1% |
| Japan | 3 | 1% |
| Italy | 2 | <1% |
| Germany | 2 | <1% |
| Austria | 1 | <1% |
| India | 1 | <1% |
| Other | 7 | 3% |
| Unknown | 209 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 63 | 26% |
| Student > Ph. D. Student | 54 | 22% |
| Student > Master | 35 | 15% |
| Student > Bachelor | 28 | 12% |
| Other | 11 | 5% |
| Other | 30 | 12% |
| Unknown | 20 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 121 | 50% |
| Biochemistry, Genetics and Molecular Biology | 32 | 13% |
| Computer Science | 22 | 9% |
| Environmental Science | 10 | 4% |
| Engineering | 6 | 2% |
| Other | 20 | 8% |
| Unknown | 30 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 26 March 2014.
All research outputs
#6,122,379
of 22,712,476 outputs
Outputs from BMC Bioinformatics
#2,323
of 7,259 outputs
Outputs of similar age
#34,077
of 110,319 outputs
Outputs of similar age from BMC Bioinformatics
#22
of 85 outputs
Altmetric has tracked 22,712,476 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 7,259 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 gotten more attention than average, scoring higher than 67% 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 110,319 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 85 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.