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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Non-canonical protein-DNA interactions identified by ChIP are not artifacts
|
|---|---|
| Published in |
BMC Genomics, April 2013
|
| DOI | 10.1186/1471-2164-14-254 |
| Pubmed ID | |
| Authors |
Richard P Bonocora, Devon M Fitzgerald, Anne M Stringer, Joseph T Wade |
| Abstract |
ChIP-chip and ChIP-seq are widely used methods to map protein-DNA interactions on a genomic scale in vivo. Waldminghaus and Skarstad recently reported, in this journal, a modified method for ChIP-chip. Based on a comparison of our previously-published ChIP-chip data for Escherichia coli σ32 with their own data, Waldminghaus and Skarstad concluded that many of the σ32 targets identified in our earlier work are false positives. In particular, we identified many non-canonical σ32 targets that are located inside genes or are associated with genes that show no detectable regulation by σ32. Waldminghaus and Skarstad propose that such non-canonical sites are artifacts, identified due to flaws in the standard ChIP methodology. Waldminghaus and Skarstad suggest specific changes to the standard ChIP procedure that reportedly eliminate the claimed artifacts. |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 3 | 33% |
| United States | 2 | 22% |
| Germany | 1 | 11% |
| France | 1 | 11% |
| Unknown | 2 | 22% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 5 | 56% |
| Members of the public | 4 | 44% |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 10% |
| Unknown | 27 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 33% |
| Researcher | 8 | 27% |
| Other | 4 | 13% |
| Student > Doctoral Student | 3 | 10% |
| Professor > Associate Professor | 2 | 7% |
| Other | 2 | 7% |
| Unknown | 1 | 3% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 17 | 57% |
| Biochemistry, Genetics and Molecular Biology | 8 | 27% |
| Immunology and Microbiology | 3 | 10% |
| Social Sciences | 1 | 3% |
| Unknown | 1 | 3% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 16 April 2013.
All research outputs
#6,623,520
of 23,577,761 outputs
Outputs from BMC Genomics
#2,912
of 10,787 outputs
Outputs of similar age
#54,574
of 198,920 outputs
Outputs of similar age from BMC Genomics
#32
of 123 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 10,787 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 72% 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 198,920 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 72% of its contemporaries.
We're also able to compare this research output to 123 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 73% of its contemporaries.