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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Exploring the transcription factor activity in high-throughput gene expression data using RLQ analysis
|
|---|---|
| Published in |
BMC Bioinformatics, June 2013
|
| DOI | 10.1186/1471-2105-14-178 |
| Pubmed ID | |
| Authors |
Florent Baty, Jochen Rüdiger, Nicola Miglino, Lukas Kern, Peter Borger, Martin Brutsche |
| Abstract |
Interpretation of gene expression microarray data in the light of external information on both columns and rows (experimental variables and gene annotations) facilitates the extraction of pertinent information hidden in these complex data. Biologists classically interpret genes of interest after retrieving functional information from a subset of genes of interest. Transcription factors play an important role in orchestrating the regulation of gene expression. Their activity can be deduced by examining the presence of putative transcription factors binding sites in the gene promoter regions. |
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 % |
|---|---|---|
| Norway | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 5% |
| United States | 1 | 5% |
| Unknown | 20 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 45% |
| Researcher | 5 | 23% |
| Professor | 2 | 9% |
| Student > Doctoral Student | 2 | 9% |
| Student > Master | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 1 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 45% |
| Biochemistry, Genetics and Molecular Biology | 3 | 14% |
| Medicine and Dentistry | 3 | 14% |
| Computer Science | 3 | 14% |
| Environmental Science | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 2 | 9% |
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 11 June 2013.
All research outputs
#17,689,573
of 22,711,645 outputs
Outputs from BMC Bioinformatics
#5,919
of 7,259 outputs
Outputs of similar age
#141,815
of 197,654 outputs
Outputs of similar age from BMC Bioinformatics
#88
of 109 outputs
Altmetric has tracked 22,711,645 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,259 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 13th percentile – i.e., 13% 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 197,654 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 109 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.