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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MMDiff: quantitative testing for shape changes in ChIP-Seq data sets
|
|---|---|
| Published in |
BMC Genomics, November 2013
|
| DOI | 10.1186/1471-2164-14-826 |
| Pubmed ID | |
| Authors |
Gabriele Schweikert, Botond Cseke, Thomas Clouaire, Adrian Bird, Guido Sanguinetti |
| Abstract |
Cell-specific gene expression is controlled by epigenetic modifications and transcription factor binding. While genome-wide maps for these protein-DNA interactions have become widely available, quantitative comparison of the resulting ChIP-Seq data sets remains challenging. Current approaches to detect differentially bound or modified regions are mainly borrowed from RNA-Seq data analysis, thus focusing on total counts of fragments mapped to a region, ignoring any information encoded in the shape of the peaks. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 20% |
| India | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 2 | 2% |
| United Kingdom | 2 | 2% |
| United States | 2 | 2% |
| Norway | 1 | 1% |
| Sweden | 1 | 1% |
| Hong Kong | 1 | 1% |
| China | 1 | 1% |
| Australia | 1 | 1% |
| Unknown | 87 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 36 | 37% |
| Researcher | 19 | 19% |
| Student > Master | 8 | 8% |
| Student > Bachelor | 6 | 6% |
| Professor > Associate Professor | 6 | 6% |
| Other | 14 | 14% |
| Unknown | 9 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 53 | 54% |
| Biochemistry, Genetics and Molecular Biology | 12 | 12% |
| Computer Science | 12 | 12% |
| Mathematics | 5 | 5% |
| Engineering | 3 | 3% |
| Other | 4 | 4% |
| Unknown | 9 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 28 December 2013.
All research outputs
#3,201,584
of 25,371,288 outputs
Outputs from BMC Genomics
#1,023
of 11,244 outputs
Outputs of similar age
#34,901
of 315,367 outputs
Outputs of similar age from BMC Genomics
#18
of 212 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 90% of its peers.
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 315,367 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 88% of its contemporaries.
We're also able to compare this research output to 212 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.