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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The Triform algorithm: improved sensitivity and specificity in ChIP-Seq peak finding
|
|---|---|
| Published in |
BMC Bioinformatics, July 2012
|
| DOI | 10.1186/1471-2105-13-176 |
| Pubmed ID | |
| Authors |
Karl Kornacker, Morten Beck Rye, Tony Håndstad, Finn Drabløs |
| Abstract |
Chromatin immunoprecipitation combined with high-throughput sequencing (ChIP-Seq) is the most frequently used method to identify the binding sites of transcription factors. Active binding sites can be seen as peaks in enrichment profiles when the sequencing reads are mapped to a reference genome. However, the profiles are normally noisy, making it challenging to identify all significantly enriched regions in a reliable way and with an acceptable false discovery rate. |
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 % |
|---|---|---|
| United States | 3 | 60% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 40% |
| Members of the public | 2 | 40% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 6% |
| United Kingdom | 1 | 2% |
| Germany | 1 | 2% |
| Unknown | 43 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 21 | 44% |
| Professor | 6 | 13% |
| Student > Ph. D. Student | 6 | 13% |
| Student > Master | 6 | 13% |
| Other | 3 | 6% |
| Other | 5 | 10% |
| Unknown | 1 | 2% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 31 | 65% |
| Computer Science | 5 | 10% |
| Biochemistry, Genetics and Molecular Biology | 4 | 8% |
| Physics and Astronomy | 1 | 2% |
| Social Sciences | 1 | 2% |
| Other | 3 | 6% |
| Unknown | 3 | 6% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 01 August 2012.
All research outputs
#7,820,309
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#3,053
of 7,454 outputs
Outputs of similar age
#55,600
of 166,301 outputs
Outputs of similar age from BMC Bioinformatics
#33
of 96 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 7,454 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has gotten more attention than average, scoring higher than 58% 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 166,301 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 96 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.