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X Demographics
Mendeley readers
Attention Score in Context
| Title |
QuickMIRSeq: a pipeline for quick and accurate quantification of both known miRNAs and isomiRs by jointly processing multiple samples from microRNA sequencing
|
|---|---|
| Published in |
BMC Bioinformatics, March 2017
|
| DOI | 10.1186/s12859-017-1601-4 |
| Pubmed ID | |
| Authors |
Shanrong Zhao, William Gordon, Sarah Du, Chi Zhang, Wen He, Li Xi, Sachin Mathur, Michael Agostino, Theresa Paradis, David von Schack, Michael Vincent, Baohong Zhang |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 124 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | <1% |
| Unknown | 123 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 32 | 26% |
| Researcher | 31 | 25% |
| Student > Master | 14 | 11% |
| Student > Bachelor | 8 | 6% |
| Other | 7 | 6% |
| Other | 11 | 9% |
| Unknown | 21 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 51 | 41% |
| Agricultural and Biological Sciences | 20 | 16% |
| Computer Science | 11 | 9% |
| Medicine and Dentistry | 4 | 3% |
| Neuroscience | 4 | 3% |
| Other | 6 | 5% |
| Unknown | 28 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 15 October 2018.
All research outputs
#4,773,101
of 26,017,215 outputs
Outputs from BMC Bioinformatics
#1,657
of 7,793 outputs
Outputs of similar age
#76,923
of 327,436 outputs
Outputs of similar age from BMC Bioinformatics
#27
of 127 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,793 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done well, scoring higher than 78% 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 327,436 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 76% of its contemporaries.
We're also able to compare this research output to 127 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.