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Mendeley readers
Attention Score in Context
Title |
Quality versus accuracy: result of a reanalysis of protein-binding microarrays from the DREAM5 challenge by using BayesPI2 including dinucleotide interdependence
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Published in |
BMC Bioinformatics, August 2014
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DOI | 10.1186/1471-2105-15-289 |
Pubmed ID | |
Authors |
Junbai Wang |
Abstract |
Computational modeling transcription factor (TF) sequence specificity is an important research topic in regulatory genomics. A systematic comparison of 26 algorithms to learn TF-DNA binding specificity in in vitro protein-binding microarray (PBM) data was published recently, but the quality of those examined PBMs was not evaluated completely. |
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 % |
---|---|---|
Unknown | 2 | 100% |
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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Norway | 1 | 7% |
Unknown | 13 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 5 | 36% |
Student > Ph. D. Student | 4 | 29% |
Other | 1 | 7% |
Student > Master | 1 | 7% |
Student > Postgraduate | 1 | 7% |
Other | 0 | 0% |
Unknown | 2 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 7 | 50% |
Agricultural and Biological Sciences | 2 | 14% |
Immunology and Microbiology | 1 | 7% |
Engineering | 1 | 7% |
Unknown | 3 | 21% |
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 09 November 2014.
All research outputs
#18,378,085
of 22,763,032 outputs
Outputs from BMC Bioinformatics
#6,307
of 7,273 outputs
Outputs of similar age
#168,409
of 236,474 outputs
Outputs of similar age from BMC Bioinformatics
#94
of 110 outputs
Altmetric has tracked 22,763,032 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,273 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 5th percentile – i.e., 5% 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 236,474 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 110 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.