| Title |
Linear models enable powerful differential activity analysis in massively parallel reporter assays
|
|---|---|
| Published in |
BMC Genomics, March 2019
|
| DOI | 10.1186/s12864-019-5556-x |
| Pubmed ID | |
| Authors |
Leslie Myint, Dimitrios G. Avramopoulos, Loyal A. Goff, Kasper D. Hansen |
X Demographics
The data shown below were collected from the profiles of 21 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 | 9 | 43% |
| France | 1 | 5% |
| Australia | 1 | 5% |
| Canada | 1 | 5% |
| Unknown | 9 | 43% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 14 | 67% |
| Members of the public | 7 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 67 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 22 | 33% |
| Student > Bachelor | 7 | 10% |
| Researcher | 7 | 10% |
| Student > Master | 7 | 10% |
| Professor | 3 | 4% |
| Other | 7 | 10% |
| Unknown | 14 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 25 | 37% |
| Agricultural and Biological Sciences | 13 | 19% |
| Neuroscience | 3 | 4% |
| Computer Science | 2 | 3% |
| Engineering | 2 | 3% |
| Other | 6 | 9% |
| Unknown | 16 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 17 April 2019.
All research outputs
#3,083,181
of 25,754,670 outputs
Outputs from BMC Genomics
#939
of 11,319 outputs
Outputs of similar age
#65,269
of 365,913 outputs
Outputs of similar age from BMC Genomics
#20
of 202 outputs
Altmetric has tracked 25,754,670 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,319 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 91% 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 365,913 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 82% of its contemporaries.
We're also able to compare this research output to 202 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 90% of its contemporaries.