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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A method for finding single-nucleotide polymorphisms with allele frequencies in sequences of deep coverage
|
|---|---|
| Published in |
BMC Bioinformatics, September 2005
|
| DOI | 10.1186/1471-2105-6-220 |
| Pubmed ID | |
| Authors |
Jianmin Wang, Xiaoqiu Huang |
| Abstract |
The allele frequencies of single-nucleotide polymorphisms (SNPs) are needed to select an optimal subset of common SNPs for use in association studies. Sequence-based methods for finding SNPs with allele frequencies may need to handle thousands of sequences from the same genome location (sequences of deep coverage). |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Israel | 1 | 5% |
| Belgium | 1 | 5% |
| Brazil | 1 | 5% |
| Unknown | 17 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 25% |
| Student > Master | 3 | 15% |
| Student > Ph. D. Student | 3 | 15% |
| Other | 2 | 10% |
| Lecturer > Senior Lecturer | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 4 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 45% |
| Computer Science | 5 | 25% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Unknown | 5 | 25% |
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 23 September 2014.
All research outputs
#18,379,018
of 22,764,165 outputs
Outputs from BMC Bioinformatics
#6,307
of 7,273 outputs
Outputs of similar age
#55,220
of 58,674 outputs
Outputs of similar age from BMC Bioinformatics
#18
of 23 outputs
Altmetric has tracked 22,764,165 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,273 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 5th percentile – i.e., 5% 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 58,674 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.