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Mendeley readers
Attention Score in Context
| Title |
dCLIP: a computational approach for comparative CLIP-seq analyses
|
|---|---|
| Published in |
Genome Biology, January 2014
|
| DOI | 10.1186/gb-2014-15-1-r11 |
| Pubmed ID | |
| Authors |
Tao Wang, Yang Xie, Guanghua Xiao |
| Abstract |
Although comparison of RNA-protein interaction profiles across different conditions has become increasingly important to understanding the function of RNA-binding proteins (RBPs), few computational approaches have been developed for quantitative comparison of CLIP-seq datasets. Here, we present an easy-to-use command line tool, dCLIP, for quantitative CLIP-seq comparative analysis. The two-stage method implemented in dCLIP, including a modified MA normalization method and a hidden Markov model, is shown to be able to effectively identify differential binding regions of RBPs in four CLIP-seq datasets, generated by HITS-CLIP, iCLIP and PAR-CLIP protocols. dCLIP is freely available at http://qbrc.swmed.edu/software/. |
X Demographics
The data shown below were collected from the profiles of 3 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 Kingdom | 1 | 33% |
| India | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 131 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 2% |
| France | 2 | 2% |
| United States | 2 | 2% |
| Sweden | 1 | <1% |
| Austria | 1 | <1% |
| Mexico | 1 | <1% |
| United Kingdom | 1 | <1% |
| Unknown | 121 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 43 | 33% |
| Researcher | 37 | 28% |
| Student > Master | 15 | 11% |
| Professor > Associate Professor | 8 | 6% |
| Student > Bachelor | 5 | 4% |
| Other | 14 | 11% |
| Unknown | 9 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 69 | 53% |
| Biochemistry, Genetics and Molecular Biology | 27 | 21% |
| Computer Science | 14 | 11% |
| Mathematics | 3 | 2% |
| Neuroscience | 3 | 2% |
| Other | 6 | 5% |
| Unknown | 9 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 12 February 2020.
All research outputs
#6,496,106
of 25,374,647 outputs
Outputs from Genome Biology
#3,104
of 4,467 outputs
Outputs of similar age
#69,252
of 318,512 outputs
Outputs of similar age from Genome Biology
#86
of 115 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
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 30th percentile – i.e., 30% 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 318,512 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
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 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.