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Mendeley readers
Attention Score in Context
Title |
Fold change rank ordering statistics: a new method for detecting differentially expressed genes
|
---|---|
Published in |
BMC Bioinformatics, January 2014
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DOI | 10.1186/1471-2105-15-14 |
Pubmed ID | |
Authors |
Doulaye Dembélé, Philippe Kastner |
Abstract |
Different methods have been proposed for analyzing differentially expressed (DE) genes in microarray data. Methods based on statistical tests that incorporate expression level variability are used more commonly than those based on fold change (FC). However, FC based results are more reproducible and biologically relevant. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Belgium | 1 | 20% |
Norway | 1 | 20% |
Unknown | 3 | 60% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 80% |
Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 138 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 2% |
Netherlands | 1 | <1% |
Brazil | 1 | <1% |
India | 1 | <1% |
Germany | 1 | <1% |
Canada | 1 | <1% |
United Kingdom | 1 | <1% |
Spain | 1 | <1% |
Belgium | 1 | <1% |
Other | 0 | 0% |
Unknown | 127 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 38 | 28% |
Researcher | 32 | 23% |
Student > Master | 15 | 11% |
Student > Bachelor | 12 | 9% |
Student > Doctoral Student | 7 | 5% |
Other | 22 | 16% |
Unknown | 12 | 9% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 52 | 38% |
Biochemistry, Genetics and Molecular Biology | 27 | 20% |
Medicine and Dentistry | 10 | 7% |
Computer Science | 9 | 7% |
Engineering | 7 | 5% |
Other | 17 | 12% |
Unknown | 16 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 20 June 2017.
All research outputs
#12,698,145
of 22,739,983 outputs
Outputs from BMC Bioinformatics
#3,625
of 7,266 outputs
Outputs of similar age
#165,507
of 329,839 outputs
Outputs of similar age from BMC Bioinformatics
#45
of 102 outputs
Altmetric has tracked 22,739,983 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,266 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 48th percentile – i.e., 48% 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 329,839 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 102 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 54% of its contemporaries.