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X Demographics
Mendeley readers
Attention Score in Context
| Title |
snp-search: simple processing, manipulation and searching of SNPs from high-throughput sequencing
|
|---|---|
| Published in |
BMC Bioinformatics, November 2013
|
| DOI | 10.1186/1471-2105-14-326 |
| Pubmed ID | |
| Authors |
Ali Al-Shahib, Anthony Underwood |
| Abstract |
A typical bacterial pathogen genome mapping project can identify thousands of single nucleotide polymorphisms (SNP). Interpreting SNP data is complex and it is difficult to conceptualise the data contained within the large flat files that are the typical output from most SNP calling algorithms. One solution to this problem is to construct a database that can be queried using simple commands so that SNP interrogation and output is both easy and comprehensible. |
X Demographics
The data shown below were collected from the profiles of 15 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 | 20% |
| United Kingdom | 2 | 13% |
| Canada | 1 | 7% |
| Sweden | 1 | 7% |
| Mexico | 1 | 7% |
| Malawi | 1 | 7% |
| Germany | 1 | 7% |
| Norway | 1 | 7% |
| Unknown | 4 | 27% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 10 | 67% |
| Members of the public | 5 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 11% |
| France | 1 | 2% |
| Australia | 1 | 2% |
| Netherlands | 1 | 2% |
| United Kingdom | 1 | 2% |
| Sweden | 1 | 2% |
| Denmark | 1 | 2% |
| Belgium | 1 | 2% |
| Unknown | 44 | 77% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 20 | 35% |
| Student > Master | 9 | 16% |
| Student > Ph. D. Student | 8 | 14% |
| Professor | 5 | 9% |
| Other | 4 | 7% |
| Other | 8 | 14% |
| Unknown | 3 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 32 | 56% |
| Computer Science | 9 | 16% |
| Biochemistry, Genetics and Molecular Biology | 5 | 9% |
| Medicine and Dentistry | 2 | 4% |
| Unspecified | 1 | 2% |
| Other | 4 | 7% |
| Unknown | 4 | 7% |
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 14 December 2013.
All research outputs
#3,813,662
of 23,340,595 outputs
Outputs from BMC Bioinformatics
#1,415
of 7,388 outputs
Outputs of similar age
#44,107
of 305,152 outputs
Outputs of similar age from BMC Bioinformatics
#22
of 102 outputs
Altmetric has tracked 23,340,595 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 7,388 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 305,152 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 85% of its contemporaries.
We're also able to compare this research output to 102 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.