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Attention Score in Context
| Title |
Gene, pathway and network frameworks to identify epistatic interactions of single nucleotide polymorphisms derived from GWAS data
|
|---|---|
| Published in |
BMC Systems Biology, December 2012
|
| DOI | 10.1186/1752-0509-6-s3-s15 |
| Pubmed ID | |
| Authors |
Yu Liu, Sean Maxwell, Tao Feng, Xiaofeng Zhu, Robert C Elston, Mehmet Koyutürk, Mark R Chance |
| Abstract |
Interactions among genomic loci (also known as epistasis) have been suggested as one of the potential sources of missing heritability in single locus analysis of genome-wide association studies (GWAS). The computational burden of searching for interactions is compounded by the extremely low threshold for identifying significant p-values due to multiple hypothesis testing corrections. Utilizing prior biological knowledge to restrict the set of candidate SNP pairs to be tested can alleviate this problem, but systematic studies that investigate the relative merits of integrating different biological frameworks and GWAS data have not been conducted. |
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 States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 6% |
| Switzerland | 1 | 1% |
| Brazil | 1 | 1% |
| Italy | 1 | 1% |
| Israel | 1 | 1% |
| Sweden | 1 | 1% |
| Unknown | 82 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 34 | 37% |
| Researcher | 19 | 20% |
| Student > Master | 12 | 13% |
| Professor > Associate Professor | 6 | 6% |
| Professor | 5 | 5% |
| Other | 13 | 14% |
| Unknown | 4 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 40 | 43% |
| Medicine and Dentistry | 13 | 14% |
| Computer Science | 12 | 13% |
| Biochemistry, Genetics and Molecular Biology | 10 | 11% |
| Neuroscience | 3 | 3% |
| Other | 7 | 8% |
| Unknown | 8 | 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 19 January 2013.
All research outputs
#18,326,065
of 22,693,205 outputs
Outputs from BMC Systems Biology
#834
of 1,142 outputs
Outputs of similar age
#203,097
of 261,299 outputs
Outputs of similar age from BMC Systems Biology
#41
of 56 outputs
Altmetric has tracked 22,693,205 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 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 11th percentile – i.e., 11% 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 261,299 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.