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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Evaluation and optimisation of indel detection workflows for ion torrent sequencing of the BRCA1 and BRCA2 genes
|
|---|---|
| Published in |
BMC Genomics, June 2014
|
| DOI | 10.1186/1471-2164-15-516 |
| Pubmed ID | |
| Authors |
Zhen Xuan Yeo, Joshua Chee Leong Wong, Steven G Rozen, Ann Siew Gek Lee |
| Abstract |
The Ion Torrent PGM is a popular benchtop sequencer that shows promise in replacing conventional Sanger sequencing as the gold standard for mutation detection. Despite the PGM's reported high accuracy in calling single nucleotide variations, it tends to generate many false positive calls in detecting insertions and deletions (indels), which may hinder its utility for clinical genetic testing. |
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 % |
|---|---|---|
| Canada | 1 | 33% |
| United Kingdom | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 33% |
| Scientists | 1 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 4% |
| Germany | 1 | 1% |
| Switzerland | 1 | 1% |
| Iceland | 1 | 1% |
| Italy | 1 | 1% |
| Spain | 1 | 1% |
| Slovenia | 1 | 1% |
| Unknown | 90 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 27 | 27% |
| Student > Ph. D. Student | 24 | 24% |
| Student > Bachelor | 12 | 12% |
| Other | 9 | 9% |
| Student > Master | 8 | 8% |
| Other | 12 | 12% |
| Unknown | 8 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 40 | 40% |
| Biochemistry, Genetics and Molecular Biology | 26 | 26% |
| Medicine and Dentistry | 10 | 10% |
| Computer Science | 6 | 6% |
| Engineering | 3 | 3% |
| Other | 7 | 7% |
| Unknown | 8 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 01 July 2014.
All research outputs
#15,302,068
of 22,757,541 outputs
Outputs from BMC Genomics
#6,675
of 10,637 outputs
Outputs of similar age
#133,725
of 228,106 outputs
Outputs of similar age from BMC Genomics
#107
of 199 outputs
Altmetric has tracked 22,757,541 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,637 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
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 228,106 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 199 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.