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Mendeley readers
Attention Score in Context
| Title |
A probabilistic method for identifying rare variants underlying complex traits
|
|---|---|
| Published in |
BMC Genomics, January 2013
|
| DOI | 10.1186/1471-2164-14-s1-s11 |
| Pubmed ID | |
| Authors |
Jiayin Wang, Zhongmeng Zhao, Zhi Cao, Aiyuan Yang, Jin Zhang |
| Abstract |
Identifying the genetic variants that contribute to disease susceptibilities is important both for developing methodologies and for studying complex diseases in molecular biology. It has been demonstrated that the spectrum of minor allelic frequencies (MAFs) of risk genetic variants ranges from common to rare. Although association studies are shifting to incorporate rare variants (RVs) affecting complex traits, existing approaches do not show a high degree of success, and more efforts should be considered. |
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 % |
|---|---|---|
| United Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 5% |
| Hong Kong | 1 | 5% |
| United States | 1 | 5% |
| Sweden | 1 | 5% |
| Unknown | 18 | 82% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 36% |
| Student > Ph. D. Student | 5 | 23% |
| Student > Doctoral Student | 2 | 9% |
| Student > Master | 2 | 9% |
| Lecturer > Senior Lecturer | 1 | 5% |
| Other | 3 | 14% |
| Unknown | 1 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 11 | 50% |
| Biochemistry, Genetics and Molecular Biology | 4 | 18% |
| Medicine and Dentistry | 2 | 9% |
| Computer Science | 1 | 5% |
| Decision Sciences | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 2 | 9% |
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 06 March 2013.
All research outputs
#20,656,161
of 25,373,627 outputs
Outputs from BMC Genomics
#8,709
of 11,244 outputs
Outputs of similar age
#226,247
of 287,026 outputs
Outputs of similar age from BMC Genomics
#133
of 186 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 12th percentile – i.e., 12% 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 287,026 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 186 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.