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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A Parzen window-based approach for the detection of locally enriched transcription factor binding sites
|
|---|---|
| Published in |
BMC Bioinformatics, January 2013
|
| DOI | 10.1186/1471-2105-14-26 |
| Pubmed ID | |
| Authors |
Alexis Vandenbon, Yutaro Kumagai, Shunsuke Teraguchi, Karlou Mar Amada, Shizuo Akira, Daron M Standley |
| Abstract |
Identification of cis- and trans-acting factors regulating gene expression remains an important problem in biology. Bioinformatics analyses of regulatory regions are hampered by several difficulties. One is that binding sites for regulatory proteins are often not significantly over-represented in the set of DNA sequences of interest, because of high levels of false positive predictions, and because of positional restrictions on functional binding sites with regard to the transcription start site. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Norway | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 5% |
| Unknown | 19 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 9 | 45% |
| Student > Ph. D. Student | 3 | 15% |
| Professor | 2 | 10% |
| Student > Bachelor | 2 | 10% |
| Student > Master | 2 | 10% |
| Other | 2 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 35% |
| Computer Science | 5 | 25% |
| Biochemistry, Genetics and Molecular Biology | 3 | 15% |
| Engineering | 2 | 10% |
| Medicine and Dentistry | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 2 | 10% |
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 21 January 2013.
All research outputs
#20,178,948
of 22,693,205 outputs
Outputs from BMC Bioinformatics
#6,827
of 7,254 outputs
Outputs of similar age
#246,621
of 279,301 outputs
Outputs of similar age from BMC Bioinformatics
#137
of 146 outputs
Altmetric has tracked 22,693,205 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,254 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 1st percentile – i.e., 1% 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 279,301 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 146 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.