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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Error-correcting properties of the SOLiD Exact Call Chemistry
|
|---|---|
| Published in |
BMC Bioinformatics, June 2012
|
| DOI | 10.1186/1471-2105-13-145 |
| Pubmed ID | |
| Authors |
Tim Massingham, Nick Goldman |
| Abstract |
The Exact Call Chemistry for the SOLiD Next-Generation Sequencing platform augments the two-base-encoding chemistry with an additional round of ligation, using an alternative set of probes, that allows some mistakes made when reading the first set of probes to be corrected. Additionally, the Exact Call Chemistry allows reads produced by the platform to be decoded directly into nucleotide sequence rather than its two-base 'color' encoding. |
X Demographics
The data shown below were collected from the profiles of 8 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 | 38% |
| Netherlands | 2 | 25% |
| Unknown | 3 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 50% |
| Scientists | 4 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 11% |
| United Kingdom | 1 | 3% |
| Germany | 1 | 3% |
| Unknown | 32 | 84% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 37% |
| Other | 4 | 11% |
| Student > Ph. D. Student | 4 | 11% |
| Student > Bachelor | 3 | 8% |
| Professor | 3 | 8% |
| Other | 8 | 21% |
| Unknown | 2 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 23 | 61% |
| Biochemistry, Genetics and Molecular Biology | 3 | 8% |
| Computer Science | 2 | 5% |
| Medicine and Dentistry | 2 | 5% |
| Business, Management and Accounting | 1 | 3% |
| Other | 5 | 13% |
| Unknown | 2 | 5% |
Attention Score in Context
This research output has an Altmetric Attention Score of 25. 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 28 April 2021.
All research outputs
#1,292,098
of 22,669,724 outputs
Outputs from BMC Bioinformatics
#199
of 7,247 outputs
Outputs of similar age
#7,800
of 164,330 outputs
Outputs of similar age from BMC Bioinformatics
#6
of 103 outputs
Altmetric has tracked 22,669,724 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,247 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 97% 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 164,330 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 95% of its contemporaries.
We're also able to compare this research output to 103 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.