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Mendeley readers
Attention Score in Context
| Title |
ChIPseqR: analysis of ChIP-seq experiments
|
|---|---|
| Published in |
BMC Bioinformatics, January 2011
|
| DOI | 10.1186/1471-2105-12-39 |
| Pubmed ID | |
| Authors |
Peter Humburg, Chris A Helliwell, David Bulger, Glenn Stone |
| Abstract |
The use of high-throughput sequencing in combination with chromatin immunoprecipitation (ChIP-seq) has enabled the study of genome-wide protein binding at high resolution. While the amount of data generated from such experiments is steadily increasing, the methods available for their analysis remain limited. Although several algorithms for the analysis of ChIP-seq data have been published they focus almost exclusively on transcription factor studies and are usually not well suited for the analysis of other types of experiments. |
Mendeley readers
The data shown below were compiled from readership statistics for 162 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 4% |
| United Kingdom | 5 | 3% |
| France | 4 | 2% |
| Germany | 2 | 1% |
| China | 2 | 1% |
| Australia | 1 | <1% |
| Canada | 1 | <1% |
| Argentina | 1 | <1% |
| Denmark | 1 | <1% |
| Other | 5 | 3% |
| Unknown | 133 | 82% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 65 | 40% |
| Student > Ph. D. Student | 38 | 23% |
| Professor | 13 | 8% |
| Student > Master | 12 | 7% |
| Professor > Associate Professor | 8 | 5% |
| Other | 22 | 14% |
| Unknown | 4 | 2% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 110 | 68% |
| Biochemistry, Genetics and Molecular Biology | 23 | 14% |
| Computer Science | 10 | 6% |
| Medicine and Dentistry | 8 | 5% |
| Mathematics | 4 | 2% |
| Other | 4 | 2% |
| Unknown | 3 | 2% |
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 15 February 2011.
All research outputs
#20,143,522
of 22,649,029 outputs
Outputs from BMC Bioinformatics
#6,808
of 7,234 outputs
Outputs of similar age
#171,581
of 182,378 outputs
Outputs of similar age from BMC Bioinformatics
#39
of 44 outputs
Altmetric has tracked 22,649,029 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 7,234 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 182,378 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 44 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.