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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Algorithm-driven Artifacts in median polish summarization of Microarray data
|
|---|---|
| Published in |
BMC Bioinformatics, November 2010
|
| DOI | 10.1186/1471-2105-11-553 |
| Pubmed ID | |
| Authors |
Federico M Giorgi, Anthony M Bolger, Marc Lohse, Bjoern Usadel |
| Abstract |
High-throughput measurement of transcript intensities using Affymetrix type oligonucleotide microarrays has produced a massive quantity of data during the last decade. Different preprocessing techniques exist to convert the raw signal intensities measured by these chips into gene expression estimates. Although these techniques have been widely benchmarked in the context of differential gene expression analysis, there are only few examples where their performance has been assessed in respect to coexpression-based studies such as sample classification. |
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 % |
|---|---|---|
| Italy | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 2 | 2% |
| United Kingdom | 2 | 2% |
| Portugal | 1 | 1% |
| France | 1 | 1% |
| Switzerland | 1 | 1% |
| Germany | 1 | 1% |
| Belgium | 1 | 1% |
| Denmark | 1 | 1% |
| Russia | 1 | 1% |
| Other | 1 | 1% |
| Unknown | 86 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 33 | 34% |
| Researcher | 24 | 24% |
| Student > Master | 11 | 11% |
| Other | 5 | 5% |
| Student > Bachelor | 4 | 4% |
| Other | 9 | 9% |
| Unknown | 12 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 41 | 42% |
| Computer Science | 14 | 14% |
| Biochemistry, Genetics and Molecular Biology | 11 | 11% |
| Medicine and Dentistry | 6 | 6% |
| Environmental Science | 2 | 2% |
| Other | 6 | 6% |
| Unknown | 18 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 05 January 2021.
All research outputs
#4,664,467
of 22,655,397 outputs
Outputs from BMC Bioinformatics
#1,803
of 7,236 outputs
Outputs of similar age
#21,323
of 100,840 outputs
Outputs of similar age from BMC Bioinformatics
#15
of 65 outputs
Altmetric has tracked 22,655,397 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,236 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 gotten more attention than average, scoring higher than 73% 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 100,840 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 65 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 72% of its contemporaries.