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Mendeley readers
Attention Score in Context
| Title |
Epigenetic priors for identifying active transcription factor binding sites
|
|---|---|
| Published in |
Bioinformatics, November 2011
|
| DOI | 10.1093/bioinformatics/btr614 |
| Pubmed ID | |
| Authors |
Gabriel Cuellar-Partida, Fabian A. Buske, Robert C. McLeay, Tom Whitington, William Stafford Noble, Timothy L. Bailey |
| Abstract |
Accurate knowledge of the genome-wide binding of transcription factors in a particular cell type or under a particular condition is necessary for understanding transcriptional regulation. Using epigenetic data such as histone modification and DNase I, accessibility data has been shown to improve motif-based in silico methods for predicting such binding, but this approach has not yet been fully explored. |
Mendeley readers
The data shown below were compiled from readership statistics for 192 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 3% |
| Germany | 1 | <1% |
| Italy | 1 | <1% |
| Hong Kong | 1 | <1% |
| Finland | 1 | <1% |
| France | 1 | <1% |
| Canada | 1 | <1% |
| United Kingdom | 1 | <1% |
| Spain | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 178 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 53 | 28% |
| Researcher | 42 | 22% |
| Student > Master | 25 | 13% |
| Student > Bachelor | 15 | 8% |
| Professor > Associate Professor | 9 | 5% |
| Other | 25 | 13% |
| Unknown | 23 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 84 | 44% |
| Biochemistry, Genetics and Molecular Biology | 34 | 18% |
| Computer Science | 19 | 10% |
| Medicine and Dentistry | 6 | 3% |
| Physics and Astronomy | 3 | 2% |
| Other | 14 | 7% |
| Unknown | 32 | 17% |
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 19 July 2021.
All research outputs
#8,534,976
of 25,374,647 outputs
Outputs from Bioinformatics
#6,956
of 12,808 outputs
Outputs of similar age
#52,779
of 155,101 outputs
Outputs of similar age from Bioinformatics
#66
of 127 outputs
Altmetric has tracked 25,374,647 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 12,808 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one is in the 34th percentile – i.e., 34% 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 155,101 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 127 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.