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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The limit fold change model: A practical approach for selecting differentially expressed genes from microarray data
|
|---|---|
| Published in |
BMC Bioinformatics, June 2002
|
| DOI | 10.1186/1471-2105-3-17 |
| Pubmed ID | |
| Authors |
David M Mutch, Alvin Berger, Robert Mansourian, Andreas Rytz, Matthew-Alan Roberts |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 50% |
| United States | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 151 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 3% |
| France | 3 | 2% |
| United States | 3 | 2% |
| Italy | 3 | 2% |
| Netherlands | 1 | <1% |
| Brazil | 1 | <1% |
| Sweden | 1 | <1% |
| Germany | 1 | <1% |
| India | 1 | <1% |
| Other | 3 | 2% |
| Unknown | 130 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 39 | 26% |
| Student > Ph. D. Student | 34 | 23% |
| Student > Master | 13 | 9% |
| Student > Doctoral Student | 9 | 6% |
| Professor > Associate Professor | 8 | 5% |
| Other | 25 | 17% |
| Unknown | 23 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 60 | 40% |
| Medicine and Dentistry | 17 | 11% |
| Biochemistry, Genetics and Molecular Biology | 14 | 9% |
| Computer Science | 11 | 7% |
| Engineering | 7 | 5% |
| Other | 19 | 13% |
| Unknown | 23 | 15% |
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 15 September 2022.
All research outputs
#17,218,945
of 25,287,709 outputs
Outputs from BMC Bioinformatics
#5,638
of 7,672 outputs
Outputs of similar age
#43,186
of 47,579 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 1 outputs
Altmetric has tracked 25,287,709 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,672 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 18th percentile – i.e., 18% 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 47,579 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them