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Mendeley readers
Attention Score in Context
Title |
Genetic studies of complex human diseases: Characterizing SNP-disease associations using Bayesian networks
|
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Published in |
BMC Systems Biology, December 2012
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DOI | 10.1186/1752-0509-6-s3-s14 |
Pubmed ID | |
Authors |
Bing Han, Xue-wen Chen, Zohreh Talebizadeh, Hua Xu |
Abstract |
Detecting epistatic interactions plays a significant role in improving pathogenesis, prevention, diagnosis, and treatment of complex human diseases. Applying machine learning or statistical methods to epistatic interaction detection will encounter some common problems, e.g., very limited number of samples, an extremely high search space, a large number of false positives, and ways to measure the association between disease markers and the phenotype. |
Mendeley readers
The data shown below were compiled from readership statistics for 145 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Brazil | 2 | 1% |
United States | 2 | 1% |
Ireland | 1 | <1% |
United Kingdom | 1 | <1% |
France | 1 | <1% |
Unknown | 138 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 30 | 21% |
Student > Master | 25 | 17% |
Researcher | 23 | 16% |
Student > Postgraduate | 11 | 8% |
Student > Bachelor | 11 | 8% |
Other | 22 | 15% |
Unknown | 23 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 26 | 18% |
Medicine and Dentistry | 23 | 16% |
Biochemistry, Genetics and Molecular Biology | 16 | 11% |
Computer Science | 12 | 8% |
Engineering | 8 | 6% |
Other | 32 | 22% |
Unknown | 28 | 19% |
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 11 January 2013.
All research outputs
#23,010,126
of 25,654,806 outputs
Outputs from BMC Systems Biology
#1,003
of 1,132 outputs
Outputs of similar age
#248,193
of 277,232 outputs
Outputs of similar age from BMC Systems Biology
#35
of 37 outputs
Altmetric has tracked 25,654,806 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,132 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 1st percentile – i.e., 1% 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 277,232 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.