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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Thawing Frozen Robust Multi-array Analysis (fRMA)
|
|---|---|
| Published in |
BMC Bioinformatics, September 2011
|
| DOI | 10.1186/1471-2105-12-369 |
| Pubmed ID | |
| Authors |
Matthew N McCall, Rafael A Irizarry |
| Abstract |
A novel method of microarray preprocessing--Frozen Robust Multi-array Analysis (fRMA)--has recently been developed. This algorithm allows the user to preprocess arrays individually while retaining the advantages of multi-array preprocessing methods. The frozen parameter estimates required by this algorithm are generated using a large database of publicly available arrays. Curation of such a database and creation of the frozen parameter estimates is time-consuming; therefore, fRMA has only been implemented on the most widely used Affymetrix platforms. |
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 % |
|---|---|---|
| Canada | 1 | 25% |
| United States | 1 | 25% |
| Unknown | 2 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 3 | 4% |
| United Kingdom | 2 | 3% |
| France | 1 | 1% |
| South Africa | 1 | 1% |
| Portugal | 1 | 1% |
| Canada | 1 | 1% |
| Denmark | 1 | 1% |
| Spain | 1 | 1% |
| United States | 1 | 1% |
| Other | 0 | 0% |
| Unknown | 56 | 82% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 29% |
| Researcher | 16 | 24% |
| Student > Master | 7 | 10% |
| Student > Bachelor | 7 | 10% |
| Student > Doctoral Student | 3 | 4% |
| Other | 8 | 12% |
| Unknown | 7 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 27 | 40% |
| Computer Science | 8 | 12% |
| Biochemistry, Genetics and Molecular Biology | 7 | 10% |
| Medicine and Dentistry | 7 | 10% |
| Mathematics | 5 | 7% |
| Other | 6 | 9% |
| Unknown | 8 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 21 November 2023.
All research outputs
#3,134,639
of 22,893,031 outputs
Outputs from BMC Bioinformatics
#1,135
of 7,299 outputs
Outputs of similar age
#15,060
of 114,725 outputs
Outputs of similar age from BMC Bioinformatics
#16
of 89 outputs
Altmetric has tracked 22,893,031 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,299 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 84% 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 114,725 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 86% of its contemporaries.
We're also able to compare this research output to 89 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.