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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Advancing the functional utility of PAR-CLIP by quantifying background binding to mRNAs and lncRNAs
|
|---|---|
| Published in |
Genome Biology, January 2014
|
| DOI | 10.1186/gb-2014-15-1-r2 |
| Pubmed ID | |
| Authors |
Matthew B Friedersdorf, Jack D Keene |
| Abstract |
Sequence specific RNA binding proteins are important regulators of gene expression. Several related crosslinking-based, high-throughput sequencing methods, including PAR-CLIP, have recently been developed to determine direct binding sites of global protein-RNA interactions. However, no studies have quantitatively addressed the contribution of background binding to datasets produced by these methods. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 50% |
| Austria | 1 | 25% |
| United Kingdom | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 1 | 25% |
| Science communicators (journalists, bloggers, editors) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 165 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Denmark | 2 | 1% |
| Switzerland | 1 | <1% |
| France | 1 | <1% |
| Germany | 1 | <1% |
| United Kingdom | 1 | <1% |
| Austria | 1 | <1% |
| Spain | 1 | <1% |
| United States | 1 | <1% |
| Unknown | 156 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 59 | 36% |
| Researcher | 39 | 24% |
| Student > Master | 14 | 8% |
| Professor | 11 | 7% |
| Student > Bachelor | 8 | 5% |
| Other | 21 | 13% |
| Unknown | 13 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 66 | 40% |
| Biochemistry, Genetics and Molecular Biology | 54 | 33% |
| Computer Science | 13 | 8% |
| Medicine and Dentistry | 4 | 2% |
| Chemistry | 4 | 2% |
| Other | 7 | 4% |
| Unknown | 17 | 10% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 15 May 2016.
All research outputs
#15,740,505
of 25,374,917 outputs
Outputs from Genome Biology
#3,967
of 4,467 outputs
Outputs of similar age
#182,612
of 318,514 outputs
Outputs of similar age from Genome Biology
#105
of 115 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 10th percentile – i.e., 10% 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 318,514 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 115 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.