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Mendeley readers
Attention Score in Context
| Title |
CANGS: a user-friendly utility for processing and analyzing 454 GS-FLX data in biodiversity studies
|
|---|---|
| Published in |
BMC Research Notes, January 2010
|
| DOI | 10.1186/1756-0500-3-3 |
| Pubmed ID | |
| Authors |
Ram Vinay Pandey, Viola Nolte, Christian Schlötterer |
| Abstract |
Next generation sequencing (NGS) technologies have substantially increased the sequence output while the costs were dramatically reduced. In addition to the use in whole genome sequencing, the 454 GS-FLX platform is becoming a widely used tool for biodiversity surveys based on amplicon sequencing. In order to use NGS for biodiversity surveys, software tools are required, which perform quality control, trimming of the sequence reads, removal of PCR primers, and generation of input files for downstream analyses. A user-friendly software utility that carries out these steps is still lacking. |
Mendeley readers
The data shown below were compiled from readership statistics for 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 5% |
| Germany | 4 | 3% |
| Spain | 3 | 2% |
| Sweden | 2 | 2% |
| France | 2 | 2% |
| Brazil | 1 | <1% |
| United Kingdom | 1 | <1% |
| Argentina | 1 | <1% |
| Italy | 1 | <1% |
| Other | 2 | 2% |
| Unknown | 105 | 82% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 38 | 30% |
| Student > Ph. D. Student | 20 | 16% |
| Student > Master | 14 | 11% |
| Professor > Associate Professor | 13 | 10% |
| Professor | 10 | 8% |
| Other | 25 | 20% |
| Unknown | 8 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 84 | 66% |
| Biochemistry, Genetics and Molecular Biology | 13 | 10% |
| Immunology and Microbiology | 5 | 4% |
| Environmental Science | 4 | 3% |
| Computer Science | 3 | 2% |
| Other | 11 | 9% |
| Unknown | 8 | 6% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 09 August 2010.
All research outputs
#14,598,593
of 25,368,786 outputs
Outputs from BMC Research Notes
#1,721
of 4,513 outputs
Outputs of similar age
#138,507
of 173,326 outputs
Outputs of similar age from BMC Research Notes
#11
of 17 outputs
Altmetric has tracked 25,368,786 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,513 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has gotten more attention than average, scoring higher than 61% 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 173,326 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.