You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Feature selection and causal analysis for microbiome studies in the presence of confounding using standardization
|
|---|---|
| Published in |
BMC Bioinformatics, July 2021
|
| DOI | 10.1186/s12859-021-04232-2 |
| Pubmed ID | |
| Authors |
Emily Goren, Chong Wang, Zhulin He, Amy M. Sheflin, Dawn Chiniquy, Jessica E. Prenni, Susannah Tringe, Daniel P. Schachtman, Peng Liu |
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 % |
|---|---|---|
| United States | 3 | 33% |
| India | 1 | 11% |
| Sweden | 1 | 11% |
| United Kingdom | 1 | 11% |
| Unknown | 3 | 33% |
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 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 27 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 22% |
| Researcher | 4 | 15% |
| Student > Postgraduate | 2 | 7% |
| Student > Bachelor | 1 | 4% |
| Unspecified | 1 | 4% |
| Other | 2 | 7% |
| Unknown | 11 | 41% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 4 | 15% |
| Biochemistry, Genetics and Molecular Biology | 3 | 11% |
| Mathematics | 2 | 7% |
| Agricultural and Biological Sciences | 2 | 7% |
| Environmental Science | 1 | 4% |
| Other | 4 | 15% |
| Unknown | 11 | 41% |
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 14 September 2022.
All research outputs
#6,869,180
of 24,417,958 outputs
Outputs from BMC Bioinformatics
#2,506
of 7,530 outputs
Outputs of similar age
#136,940
of 429,050 outputs
Outputs of similar age from BMC Bioinformatics
#54
of 143 outputs
Altmetric has tracked 24,417,958 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 7,530 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 66% 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 429,050 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 67% of its contemporaries.
We're also able to compare this research output to 143 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 62% of its contemporaries.