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X Demographics
Mendeley readers
Attention Score in Context
| Title |
virtualArray: a R/bioconductor package to merge raw data from different microarray platforms
|
|---|---|
| Published in |
BMC Bioinformatics, March 2013
|
| DOI | 10.1186/1471-2105-14-75 |
| Pubmed ID | |
| Authors |
Andreas Heider, Rüdiger Alt |
| Abstract |
Microarrays have become a routine tool to address diverse biological questions. Therefore, different types and generations of microarrays have been produced by several manufacturers over time. Likewise, the diversity of raw data deposited in public databases such as NCBI GEO or EBI ArrayExpress has grown enormously.This has resulted in databases currently containing several hundred thousand microarray samples clustered by different species, manufacturers and chip generations. While one of the original goals of these databases was to make the data available to other researchers for independent analysis and, where appropriate, integration with their own data, current software implementations could not provide that feature.Only those data sets generated on the same chip platform can be readily combined and even here there are batch effects to be taken care of. A straightforward approach to deal with multiple chip types and batch effects has been missing.The software presented here was designed to solve both of these problems in a convenient and user friendly way. |
X Demographics
The data shown below were collected from the profiles of 15 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 States | 2 | 13% |
| United Kingdom | 2 | 13% |
| India | 1 | 7% |
| Norway | 1 | 7% |
| Finland | 1 | 7% |
| Germany | 1 | 7% |
| Australia | 1 | 7% |
| Unknown | 6 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 7 | 47% |
| Scientists | 6 | 40% |
| Practitioners (doctors, other healthcare professionals) | 2 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 139 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 2% |
| United Kingdom | 2 | 1% |
| Ukraine | 2 | 1% |
| Netherlands | 1 | <1% |
| South Africa | 1 | <1% |
| Germany | 1 | <1% |
| Malaysia | 1 | <1% |
| Belgium | 1 | <1% |
| India | 1 | <1% |
| Other | 4 | 3% |
| Unknown | 122 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 42 | 30% |
| Student > Ph. D. Student | 29 | 21% |
| Student > Master | 13 | 9% |
| Other | 11 | 8% |
| Student > Doctoral Student | 10 | 7% |
| Other | 26 | 19% |
| Unknown | 8 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 66 | 47% |
| Biochemistry, Genetics and Molecular Biology | 21 | 15% |
| Computer Science | 16 | 12% |
| Medicine and Dentistry | 9 | 6% |
| Mathematics | 4 | 3% |
| Other | 10 | 7% |
| Unknown | 13 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 19 November 2015.
All research outputs
#3,904,011
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#1,416
of 7,454 outputs
Outputs of similar age
#31,751
of 196,319 outputs
Outputs of similar age from BMC Bioinformatics
#27
of 159 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,454 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 81% 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 196,319 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 83% of its contemporaries.
We're also able to compare this research output to 159 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.