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Mendeley readers
Attention Score in Context
| Title |
The pitfalls of platform comparison: DNA copy number array technologies assessed
|
|---|---|
| Published in |
BMC Genomics, December 2009
|
| DOI | 10.1186/1471-2164-10-588 |
| Pubmed ID | |
| Authors |
Christina Curtis, Andy G Lynch, Mark J Dunning, Inmaculada Spiteri, John C Marioni, James Hadfield, Suet-Feung Chin, James D Brenton, Simon Tavaré, Carlos Caldas |
| Abstract |
The accurate and high resolution mapping of DNA copy number aberrations has become an important tool by which to gain insight into the mechanisms of tumourigenesis. There are various commercially available platforms for such studies, but there remains no general consensus as to the optimal platform. There have been several previous platform comparison studies, but they have either described older technologies, used less-complex samples, or have not addressed the issue of the inherent biases in such comparisons. Here we describe a systematic comparison of data from four leading microarray technologies (the Affymetrix Genome-wide SNP 5.0 array, Agilent High-Density CGH Human 244A array, Illumina HumanCNV370-Duo DNA Analysis BeadChip, and the Nimblegen 385 K oligonucleotide array). We compare samples derived from primary breast tumours and their corresponding matched normals, well-established cancer cell lines, and HapMap individuals. By careful consideration and avoidance of potential sources of bias, we aim to provide a fair assessment of platform performance. |
Mendeley readers
The data shown below were compiled from readership statistics for 134 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 3 | 2% |
| United States | 3 | 2% |
| Canada | 2 | 1% |
| Belgium | 2 | 1% |
| Mexico | 1 | <1% |
| Finland | 1 | <1% |
| Russia | 1 | <1% |
| Italy | 1 | <1% |
| Unknown | 120 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 52 | 39% |
| Student > Ph. D. Student | 32 | 24% |
| Student > Master | 13 | 10% |
| Professor > Associate Professor | 12 | 9% |
| Other | 5 | 4% |
| Other | 14 | 10% |
| Unknown | 6 | 4% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 69 | 51% |
| Medicine and Dentistry | 20 | 15% |
| Biochemistry, Genetics and Molecular Biology | 14 | 10% |
| Computer Science | 8 | 6% |
| Mathematics | 3 | 2% |
| Other | 10 | 7% |
| Unknown | 10 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 October 2016.
All research outputs
#6,754,661
of 25,374,917 outputs
Outputs from BMC Genomics
#2,641
of 11,244 outputs
Outputs of similar age
#40,971
of 176,135 outputs
Outputs of similar age from BMC Genomics
#19
of 60 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 75% 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 176,135 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 60 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 68% of its contemporaries.