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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Characterization of whole genome amplified (WGA) DNA for use in genotyping assay development
|
|---|---|
| Published in |
BMC Genomics, June 2012
|
| DOI | 10.1186/1471-2164-13-217 |
| Pubmed ID | |
| Authors |
Tao Han, Ching-Wei Chang, Joshua C Kwekel, Ying Chen, Yun Ge, Francisco Martinez-Murillo, Donna Roscoe, Živana Težak, Reena Philip, Karen Bijwaard, James C Fuscoe |
| Abstract |
Genotyping assays often require substantial amounts of DNA. To overcome the problem of limiting amounts of available DNA, Whole Genome Amplification (WGA) methods have been developed. The multiple displacement amplification (MDA) method using Φ29 polymerase has become the preferred choice due to its high processivity and low error rate. However, the uniformity and fidelity of the amplification process across the genome has not been extensively characterized. |
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 % |
|---|---|---|
| Germany | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 3% |
| Spain | 2 | 3% |
| Taiwan | 1 | 1% |
| Sweden | 1 | 1% |
| China | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 70 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 25 | 32% |
| Student > Ph. D. Student | 19 | 24% |
| Student > Master | 8 | 10% |
| Student > Postgraduate | 4 | 5% |
| Student > Bachelor | 4 | 5% |
| Other | 8 | 10% |
| Unknown | 10 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 40 | 51% |
| Biochemistry, Genetics and Molecular Biology | 14 | 18% |
| Medicine and Dentistry | 4 | 5% |
| Business, Management and Accounting | 1 | 1% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 1% |
| Other | 4 | 5% |
| Unknown | 14 | 18% |
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 07 June 2012.
All research outputs
#20,656,161
of 25,374,647 outputs
Outputs from BMC Genomics
#8,709
of 11,244 outputs
Outputs of similar age
#139,920
of 179,216 outputs
Outputs of similar age from BMC Genomics
#97
of 136 outputs
Altmetric has tracked 25,374,647 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 179,216 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 136 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.