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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Normalization of ChIP-seq data with control
|
|---|---|
| Published in |
BMC Bioinformatics, August 2012
|
| DOI | 10.1186/1471-2105-13-199 |
| Pubmed ID | |
| Authors |
Kun Liang, Sündüz Keleş |
| Abstract |
ChIP-seq has become an important tool for identifying genome-wide protein-DNA interactions, including transcription factor binding and histone modifications. In ChIP-seq experiments, ChIP samples are usually coupled with their matching control samples. Proper normalization between the ChIP and control samples is an essential aspect of ChIP-seq data analysis. |
X Demographics
The data shown below were collected from the profiles of 6 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 | 50% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Scientists | 3 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 277 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 3% |
| Germany | 3 | 1% |
| United Kingdom | 3 | 1% |
| Sweden | 2 | <1% |
| Indonesia | 1 | <1% |
| Australia | 1 | <1% |
| Finland | 1 | <1% |
| France | 1 | <1% |
| Mexico | 1 | <1% |
| Other | 3 | 1% |
| Unknown | 254 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 83 | 30% |
| Student > Ph. D. Student | 74 | 27% |
| Student > Master | 21 | 8% |
| Student > Bachelor | 19 | 7% |
| Professor > Associate Professor | 16 | 6% |
| Other | 38 | 14% |
| Unknown | 26 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 138 | 50% |
| Biochemistry, Genetics and Molecular Biology | 66 | 24% |
| Computer Science | 17 | 6% |
| Mathematics | 7 | 3% |
| Immunology and Microbiology | 5 | 2% |
| Other | 13 | 5% |
| Unknown | 31 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 09 June 2022.
All research outputs
#4,630,994
of 22,673,450 outputs
Outputs from BMC Bioinformatics
#1,793
of 7,249 outputs
Outputs of similar age
#33,007
of 167,363 outputs
Outputs of similar age from BMC Bioinformatics
#19
of 100 outputs
Altmetric has tracked 22,673,450 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,249 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done well, scoring higher than 75% 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 167,363 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 80% of its contemporaries.
We're also able to compare this research output to 100 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.