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Attention Score in Context
Title |
Sequencing genes in silico using single nucleotide polymorphisms
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Published in |
BMC Genomic Data, January 2012
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DOI | 10.1186/1471-2156-13-6 |
Pubmed ID | |
Authors |
Xinyi Cindy Zhang, Bo Zhang, Shuying Sue Li, Xin Huang, John A Hansen, Lue Ping Zhao |
Abstract |
The advent of high throughput sequencing technology has enabled the 1000 Genomes Project Pilot 3 to generate complete sequence data for more than 906 genes and 8,140 exons representing 697 subjects. The 1000 Genomes database provides a critical opportunity for further interpreting disease associations with single nucleotide polymorphisms (SNPs) discovered from genetic association studies. Currently, direct sequencing of candidate genes or regions on a large number of subjects remains both cost- and time-prohibitive. |
X Demographics
The data shown below were collected from the profiles of 4 X users 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 | 25% |
Germany | 1 | 25% |
United States | 1 | 25% |
Japan | 1 | 25% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 2 | 50% |
Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 35 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 16 | 46% |
Student > Ph. D. Student | 6 | 17% |
Student > Master | 3 | 9% |
Lecturer | 2 | 6% |
Student > Postgraduate | 2 | 6% |
Other | 2 | 6% |
Unknown | 4 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 12 | 34% |
Biochemistry, Genetics and Molecular Biology | 6 | 17% |
Mathematics | 4 | 11% |
Computer Science | 3 | 9% |
Medicine and Dentistry | 2 | 6% |
Other | 3 | 9% |
Unknown | 5 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 22 February 2012.
All research outputs
#14,535,626
of 25,371,288 outputs
Outputs from BMC Genomic Data
#425
of 1,204 outputs
Outputs of similar age
#152,569
of 253,307 outputs
Outputs of similar age from BMC Genomic Data
#4
of 14 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one has gotten more attention than average, scoring higher than 64% of its peers.
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 253,307 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.